{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# PYTHON数据管理\n",
    "[pandas官网](http://pandas.pydata.org/)\n",
    "\n",
    "pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language. It is already well on its way toward this goal.\n",
    "\n",
    "panda 与SQL在很多地方都很相似，具体的对比可以参考[该链接](http://pandas.pydata.org/pandas-docs/stable/comparison_with_sql.html)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "solution": "hidden"
   },
   "source": [
    "## 文件读取\n",
    "\n",
    "在之前的I/O章节中给我们学习了使用open函数来打开文件，read函数用来读取数据。 但是读取进来的数据都是str的格式，非常不方便我们进行分析。 pandas提供了read_csv函数可以将文件按照固定的格式进行读取，函数能够自动解析数据类型，添加列明与索引等很多功能，能够以结构化的dataframe形式存储数据。\n",
    "\n",
    "一些注意点：\n",
    "1. 不要尝试去读取excel文件，最好使用通用的csv或者txt格式\n",
    "2. 注意编码问题，使用encoding参数\n",
    "3. 注意处理报错行"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.23.4\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd \n",
    "import pandas \n",
    "print(pandas.__version__) # 检查版本，如果太低请在终端使用 conda update pandas 命令进行升级\n",
    "#?pd.read_csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "?pd.read_csv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"NBAPlayers.txt\",sep = '\\t')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>height</th>\n",
       "      <th>weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Curly Armstrong</td>\n",
       "      <td>180.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>Indiana University</td>\n",
       "      <td>1918.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cliff Barker</td>\n",
       "      <td>188.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Yorktown</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leo Barnhorst</td>\n",
       "      <td>193.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ed Bartels</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>North Carolina State University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ralph Beard</td>\n",
       "      <td>178.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Hardinsburg</td>\n",
       "      <td>Kentucky</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Player  height  weight                          collage    born  \\\n",
       "0  Curly Armstrong   180.0    77.0               Indiana University  1918.0   \n",
       "1     Cliff Barker   188.0    83.0           University of Kentucky  1921.0   \n",
       "2    Leo Barnhorst   193.0    86.0         University of Notre Dame  1924.0   \n",
       "3       Ed Bartels   196.0    88.0  North Carolina State University  1925.0   \n",
       "4      Ralph Beard   178.0    79.0           University of Kentucky  1927.0   \n",
       "\n",
       "    birth_city birth_state  \n",
       "0          NaN         NaN  \n",
       "1     Yorktown     Indiana  \n",
       "2          NaN         NaN  \n",
       "3          NaN         NaN  \n",
       "4  Hardinsburg    Kentucky  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Player            Curly Armstrong\n",
       "height                        180\n",
       "weight                         77\n",
       "collage        Indiana University\n",
       "born                         1918\n",
       "birth_city                    NaN\n",
       "birth_state                   NaN\n",
       "Name: 0, dtype: object"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Player                   Cliff Barker\n",
       "height                            188\n",
       "weight                             83\n",
       "collage        University of Kentucky\n",
       "born                             1921\n",
       "birth_city                   Yorktown\n",
       "birth_state                   Indiana\n",
       "Name: 1, dtype: object"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## DataFrame 与 Series\n",
    "\n",
    "dataframe是二维结构化数据，series是一维数据。 dataframe有一个或者多个series组成，dataframe的一行或者一列就是一个series。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# DataFrame与Series"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Series** is a one-dimensional labeled array capable of holding any data type (integers, strings, floating point numbers, Python objects, etc.). The axis labels are collectively referred to as the index.\n",
    "\n",
    "```python\n",
    "s = pd.Series(data, index=index)\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Here, data can be many different things:\n",
    "\n",
    "* a Python dict\n",
    "* an ndarray\n",
    "* a scalar value (like 5)\n",
    "\n",
    "The passed index is a list of axis labels. Thus, this separates into a few cases depending on what data is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "name    xiaoming\n",
       "age           18\n",
       "sex         male\n",
       "dtype: object"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = {\"name\":\"xiaoming\",\"age\":18,\"sex\":\"male\"}\n",
    "pd.Series(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "name    xiaoming\n",
       "age           18\n",
       "sex         male\n",
       "dtype: object"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Series(a).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(pd.Series(a).head())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "a    5\n",
       "b    5\n",
       "c    5\n",
       "d    5\n",
       "e    5\n",
       "f    5\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.Series(5,index=list(\"abcdef\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "b = [1,2,3,4,5,6]\n",
    "s1 = pd.Series(b,index = list(\"abcdef\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2, 3, 4, 5, 6], dtype=int64)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s1.values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### DataFrame的创建\n",
    "\n",
    "**DataFrame** is a 2-dimensional labeled data structure with columns of potentially different types. You can think of it like a spreadsheet or SQL table, or a dict of Series objects. It is generally the most commonly used pandas object. Like Series, DataFrame accepts many different kinds of input:\n",
    "\n",
    "* Dict of 1D ndarrays, lists, dicts, or Series\n",
    "* 2-D numpy.ndarray\n",
    "* Structured or record ndarray\n",
    "* A Series\n",
    "* Another DataFrame\n",
    "\n",
    "Along with the data, you can optionally pass index (row labels) and columns (column labels) arguments. If you pass an index and / or columns, you are guaranteeing the index and / or columns of the resulting DataFrame. Thus, a dict of Series plus a specific index will discard all data not matching up to the passed index.\n",
    "\n",
    "If axis labels are not passed, they will be constructed from the input data based on common sense rules."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>12</td>\n",
       "      <td>xiaoming</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>13</td>\n",
       "      <td>xiaohong</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>c</th>\n",
       "      <td>14</td>\n",
       "      <td>xiaogang</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   age      name\n",
       "a   12  xiaoming\n",
       "b   13  xiaohong\n",
       "c   14  xiaogang"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = {\"name\":[\"xiaoming\",\"xiaohong\",\"xiaogang\"],\"age\":[12,13,14]}\n",
    "pd.DataFrame(data = a,index = list('abc'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "?pd.DataFrame"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>a</th>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>3</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>b</th>\n",
       "      <td>a</td>\n",
       "      <td>b</td>\n",
       "      <td>c</td>\n",
       "      <td>d</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   A  B  C  D\n",
       "a  1  2  3  4\n",
       "b  a  b  c  d"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = [[1,2,3,4],['a','b','c','d']]\n",
    "pd.DataFrame(b,columns=list(\"ABCD\"),index= list('ab'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "A    object\n",
       "B    object\n",
       "C    object\n",
       "D    object\n",
       "dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.DataFrame(b,columns=list(\"ABCD\"),index= list('ab')).dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Value</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>age</th>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>name</th>\n",
       "      <td>xiaoming</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>sex</th>\n",
       "      <td>male</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Value\n",
       "age         18\n",
       "name  xiaoming\n",
       "sex       male"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = {\"name\":\"xiaoming\",\"age\":18,\"sex\":\"male\"}\n",
    "s1 = pd.Series(a)\n",
    "\n",
    "pd.DataFrame(s1,columns=[\"Value\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "age           18\n",
       "name    xiaoming\n",
       "sex         male\n",
       "dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6</td>\n",
       "      <td>9</td>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>7</td>\n",
       "      <td>4</td>\n",
       "      <td>3</td>\n",
       "      <td>7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   A  B  C  D\n",
       "0  6  3  7  4\n",
       "1  6  9  2  6\n",
       "2  7  4  3  7"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "rng = np.random.RandomState(42)\n",
    "df = pd.DataFrame(rng.randint(0, 10, (3, 4)),columns=['A', 'B', 'C', 'D'])\n",
    "df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 常用的操作\n",
    "\n",
    "pandas对dataframe与series提供了丰富的操作方法，我们在次列出最为常用的一些。\n",
    "\n",
    "**查看属性**\n",
    "1. columns\n",
    "2. index\n",
    "3. dtypes\n",
    "4. shape\n",
    "5. size\n",
    "\n",
    "**方法使用**\n",
    "1. head\n",
    "2. tail\n",
    "3. rename\n",
    "4. replace\n",
    "5. unique_values\n",
    "6. sort_values\n",
    "7. describe\n",
    "8. max/min/sum/mean\n",
    "9. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3922"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns\n",
    "df.index\n",
    "df.dtypes\n",
    "df.shape\n",
    "df.size\n",
    "len(df)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.rename(columns={\"height\":\"Height\",\"weight\":\"Weight\"},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Curly Armstrong</td>\n",
       "      <td>180.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>Indiana University</td>\n",
       "      <td>1918.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cliff Barker</td>\n",
       "      <td>188.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Yorktown</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leo Barnhorst</td>\n",
       "      <td>193.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ed Bartels</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>North Carolina State University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ralph Beard</td>\n",
       "      <td>178.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Hardinsburg</td>\n",
       "      <td>Kentucky</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Player  Height  Weight                          collage    born  \\\n",
       "0  Curly Armstrong   180.0    77.0               Indiana University  1918.0   \n",
       "1     Cliff Barker   188.0    83.0           University of Kentucky  1921.0   \n",
       "2    Leo Barnhorst   193.0    86.0         University of Notre Dame  1924.0   \n",
       "3       Ed Bartels   196.0    88.0  North Carolina State University  1925.0   \n",
       "4      Ralph Beard   178.0    79.0           University of Kentucky  1927.0   \n",
       "\n",
       "    birth_city birth_state  \n",
       "0          NaN         NaN  \n",
       "1     Yorktown     Indiana  \n",
       "2          NaN         NaN  \n",
       "3          NaN         NaN  \n",
       "4  Hardinsburg    Kentucky  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>xiao</td>\n",
       "      <td>180.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>Indiana University</td>\n",
       "      <td>1918.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cliff Barker</td>\n",
       "      <td>188.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Yorktown</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leo Barnhorst</td>\n",
       "      <td>193.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ed Bartels</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>North Carolina State University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ralph Beard</td>\n",
       "      <td>178.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Hardinsburg</td>\n",
       "      <td>Kentucky</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Gene Berce</td>\n",
       "      <td>180.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Marquette University</td>\n",
       "      <td>1926.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Charlie Black</td>\n",
       "      <td>196.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>University of Kansas</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Arco</td>\n",
       "      <td>Idaho</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Nelson Bobb</td>\n",
       "      <td>183.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>Temple University</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Pennsylvania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Jake Bornheimer</td>\n",
       "      <td>196.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>Muhlenberg College</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>New Brunswick</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Vince Boryla</td>\n",
       "      <td>196.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>University of Denver</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>East Chicago</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Don Boven</td>\n",
       "      <td>193.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Western Michigan University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>Kalamazoo</td>\n",
       "      <td>Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Harry Boykoff</td>\n",
       "      <td>208.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>St. John's University</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Joe Bradley</td>\n",
       "      <td>190.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Oklahoma State University</td>\n",
       "      <td>1928.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Oklahoma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Bob Brannum</td>\n",
       "      <td>196.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>Michigan State University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Carl Braun</td>\n",
       "      <td>196.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Colgate University</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Frankie Brian</td>\n",
       "      <td>185.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Louisiana State University</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>Zachary</td>\n",
       "      <td>Louisiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Price Brookfield</td>\n",
       "      <td>193.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>West Texas A&amp;M University</td>\n",
       "      <td>1920.0</td>\n",
       "      <td>Floydada</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Bob Brown</td>\n",
       "      <td>193.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Miami University</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>Versailles</td>\n",
       "      <td>Ohio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Jim Browne</td>\n",
       "      <td>208.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1930.0</td>\n",
       "      <td>Midlothian</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Walt Budko</td>\n",
       "      <td>196.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>Columbia University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>Kearney</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Jack Burmaster</td>\n",
       "      <td>190.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>University of Illinois at Urbana-Champaign</td>\n",
       "      <td>1926.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Tommy Byrnes</td>\n",
       "      <td>190.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Seton Hall University</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>Teaneck</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Bill Calhoun</td>\n",
       "      <td>190.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>City College of San Francisco</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Don Carlson</td>\n",
       "      <td>183.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>University of Minnesota</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>Minneapolis</td>\n",
       "      <td>Minnesota</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Bob Carpenter</td>\n",
       "      <td>196.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>East Texas State University</td>\n",
       "      <td>1917.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Jake Carter</td>\n",
       "      <td>193.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>East Texas State University</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Al Cervi*</td>\n",
       "      <td>180.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1917.0</td>\n",
       "      <td>Buffalo</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>John Chaney</td>\n",
       "      <td>190.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>Louisiana State University</td>\n",
       "      <td>1920.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Leroy Chollet</td>\n",
       "      <td>188.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>Canisius College</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Bill Closs</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Rice University</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>Edge</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3892</th>\n",
       "      <td>Chinanu Onuaku</td>\n",
       "      <td>208.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>University of Louisville</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Baltimore</td>\n",
       "      <td>Maryland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3893</th>\n",
       "      <td>Georgios Papagiannis</td>\n",
       "      <td>216.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Amarousio</td>\n",
       "      <td>Greece</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3894</th>\n",
       "      <td>Gary Payton</td>\n",
       "      <td>193.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Oregon State University</td>\n",
       "      <td>1968.0</td>\n",
       "      <td>Oakland</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3895</th>\n",
       "      <td>Marshall Plumlee</td>\n",
       "      <td>211.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>Duke University</td>\n",
       "      <td>1990.0</td>\n",
       "      <td>Fort Wayne</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3896</th>\n",
       "      <td>Jakob Poeltl</td>\n",
       "      <td>213.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>University of Utah</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>Vienna</td>\n",
       "      <td>Austria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3897</th>\n",
       "      <td>Alex Poythress</td>\n",
       "      <td>201.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Savannah</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3898</th>\n",
       "      <td>Tim Quarterman</td>\n",
       "      <td>198.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Louisiana State University</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Savannah</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3899</th>\n",
       "      <td>Chasson Randle</td>\n",
       "      <td>188.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>Stanford University</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Rock Island</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3900</th>\n",
       "      <td>Malachi Richardson</td>\n",
       "      <td>198.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Syracuse University</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Trenton</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3901</th>\n",
       "      <td>Domantas Sabonis</td>\n",
       "      <td>211.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>Gonzaga University</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Portland</td>\n",
       "      <td>Oregon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3902</th>\n",
       "      <td>Dario Saric</td>\n",
       "      <td>208.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Sibenik</td>\n",
       "      <td>Croatia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3903</th>\n",
       "      <td>Tomas Satoransky</td>\n",
       "      <td>201.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991.0</td>\n",
       "      <td>Prague</td>\n",
       "      <td>Czech Republic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3904</th>\n",
       "      <td>Wayne Selden</td>\n",
       "      <td>196.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>University of Kansas</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Roxbury</td>\n",
       "      <td>Massachusetts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3905</th>\n",
       "      <td>Pascal Siakam</td>\n",
       "      <td>206.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>New Mexico State University</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Douala</td>\n",
       "      <td>Cameroon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3906</th>\n",
       "      <td>Diamond Stone</td>\n",
       "      <td>211.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>University of Maryland</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Milwaukee</td>\n",
       "      <td>Wisconsin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3907</th>\n",
       "      <td>Edy Tavares</td>\n",
       "      <td>211.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3908</th>\n",
       "      <td>Isaiah Taylor</td>\n",
       "      <td>190.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>University of Texas at Austin</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Hayward</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3909</th>\n",
       "      <td>Mike Tobey</td>\n",
       "      <td>213.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>University of Virginia</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Monroe</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3910</th>\n",
       "      <td>Tyler Ulis</td>\n",
       "      <td>178.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Detroit</td>\n",
       "      <td>Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3911</th>\n",
       "      <td>Jarrod Uthoff</td>\n",
       "      <td>206.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>University of Iowa</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Cedar Rapids</td>\n",
       "      <td>Iowa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3912</th>\n",
       "      <td>Denzel Valentine</td>\n",
       "      <td>198.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Michigan State University</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Lansing</td>\n",
       "      <td>Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3913</th>\n",
       "      <td>Fred VanVleet</td>\n",
       "      <td>183.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Wichita State University</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Rockford</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3914</th>\n",
       "      <td>Taurean Waller-Prince</td>\n",
       "      <td>183.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3915</th>\n",
       "      <td>Okaro White</td>\n",
       "      <td>203.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Florida State University</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>Clearwater</td>\n",
       "      <td>Florida</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3916</th>\n",
       "      <td>Isaiah Whitehead</td>\n",
       "      <td>193.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Seton Hall University</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3917</th>\n",
       "      <td>Troy Williams</td>\n",
       "      <td>198.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>South Carolina State University</td>\n",
       "      <td>1969.0</td>\n",
       "      <td>Columbia</td>\n",
       "      <td>South Carolina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3918</th>\n",
       "      <td>Kyle Wiltjer</td>\n",
       "      <td>208.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>Gonzaga University</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>Portland</td>\n",
       "      <td>Oregon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3919</th>\n",
       "      <td>Stephen Zimmerman</td>\n",
       "      <td>213.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>University of Nevada, Las Vegas</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Hendersonville</td>\n",
       "      <td>Tennessee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3920</th>\n",
       "      <td>Paul Zipser</td>\n",
       "      <td>203.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Heidelberg</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3921</th>\n",
       "      <td>Ivica Zubac</td>\n",
       "      <td>216.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Mostar</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3922 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Player  Height  Weight  \\\n",
       "0                      xiao   180.0    77.0   \n",
       "1              Cliff Barker   188.0    83.0   \n",
       "2             Leo Barnhorst   193.0    86.0   \n",
       "3                Ed Bartels   196.0    88.0   \n",
       "4               Ralph Beard   178.0    79.0   \n",
       "5                Gene Berce   180.0    79.0   \n",
       "6             Charlie Black   196.0    90.0   \n",
       "7               Nelson Bobb   183.0    77.0   \n",
       "8           Jake Bornheimer   196.0    90.0   \n",
       "9              Vince Boryla   196.0    95.0   \n",
       "10                Don Boven   193.0    95.0   \n",
       "11            Harry Boykoff   208.0   102.0   \n",
       "12              Joe Bradley   190.0    79.0   \n",
       "13              Bob Brannum   196.0    97.0   \n",
       "14               Carl Braun   196.0    81.0   \n",
       "15            Frankie Brian   185.0    81.0   \n",
       "16         Price Brookfield   193.0    83.0   \n",
       "17                Bob Brown   193.0    92.0   \n",
       "18               Jim Browne   208.0   106.0   \n",
       "19               Walt Budko   196.0    99.0   \n",
       "20           Jack Burmaster   190.0    86.0   \n",
       "21             Tommy Byrnes   190.0    79.0   \n",
       "22             Bill Calhoun   190.0    81.0   \n",
       "23              Don Carlson   183.0    77.0   \n",
       "24            Bob Carpenter   196.0    90.0   \n",
       "25              Jake Carter   193.0    88.0   \n",
       "26                Al Cervi*   180.0    77.0   \n",
       "27              John Chaney   190.0    83.0   \n",
       "28            Leroy Chollet   188.0    86.0   \n",
       "29               Bill Closs   196.0    88.0   \n",
       "...                     ...     ...     ...   \n",
       "3892         Chinanu Onuaku   208.0   111.0   \n",
       "3893   Georgios Papagiannis   216.0   108.0   \n",
       "3894            Gary Payton   193.0    81.0   \n",
       "3895       Marshall Plumlee   211.0   111.0   \n",
       "3896           Jakob Poeltl   213.0   112.0   \n",
       "3897         Alex Poythress   201.0   107.0   \n",
       "3898         Tim Quarterman   198.0    88.0   \n",
       "3899         Chasson Randle   188.0    83.0   \n",
       "3900     Malachi Richardson   198.0    92.0   \n",
       "3901       Domantas Sabonis   211.0   108.0   \n",
       "3902            Dario Saric   208.0   101.0   \n",
       "3903       Tomas Satoransky   201.0    95.0   \n",
       "3904           Wayne Selden   196.0   104.0   \n",
       "3905          Pascal Siakam   206.0   104.0   \n",
       "3906          Diamond Stone   211.0   115.0   \n",
       "3907            Edy Tavares   211.0   115.0   \n",
       "3908          Isaiah Taylor   190.0    77.0   \n",
       "3909             Mike Tobey   213.0   117.0   \n",
       "3910             Tyler Ulis   178.0    68.0   \n",
       "3911          Jarrod Uthoff   206.0   100.0   \n",
       "3912       Denzel Valentine   198.0    96.0   \n",
       "3913          Fred VanVleet   183.0    88.0   \n",
       "3914  Taurean Waller-Prince   183.0    88.0   \n",
       "3915            Okaro White   203.0    92.0   \n",
       "3916       Isaiah Whitehead   193.0    96.0   \n",
       "3917          Troy Williams   198.0    97.0   \n",
       "3918           Kyle Wiltjer   208.0   108.0   \n",
       "3919      Stephen Zimmerman   213.0   108.0   \n",
       "3920            Paul Zipser   203.0    97.0   \n",
       "3921            Ivica Zubac   216.0   120.0   \n",
       "\n",
       "                                         collage    born      birth_city  \\\n",
       "0                             Indiana University  1918.0             NaN   \n",
       "1                         University of Kentucky  1921.0        Yorktown   \n",
       "2                       University of Notre Dame  1924.0             NaN   \n",
       "3                North Carolina State University  1925.0             NaN   \n",
       "4                         University of Kentucky  1927.0     Hardinsburg   \n",
       "5                           Marquette University  1926.0             NaN   \n",
       "6                           University of Kansas  1921.0            Arco   \n",
       "7                              Temple University  1924.0    Philadelphia   \n",
       "8                             Muhlenberg College  1927.0   New Brunswick   \n",
       "9                           University of Denver  1927.0    East Chicago   \n",
       "10                   Western Michigan University  1925.0       Kalamazoo   \n",
       "11                         St. John's University  1922.0        Brooklyn   \n",
       "12                     Oklahoma State University  1928.0      Washington   \n",
       "13                     Michigan State University  1925.0             NaN   \n",
       "14                            Colgate University  1927.0        Brooklyn   \n",
       "15                    Louisiana State University  1923.0         Zachary   \n",
       "16                     West Texas A&M University  1920.0        Floydada   \n",
       "17                              Miami University  1923.0      Versailles   \n",
       "18                                           NaN  1930.0      Midlothian   \n",
       "19                           Columbia University  1925.0         Kearney   \n",
       "20    University of Illinois at Urbana-Champaign  1926.0             NaN   \n",
       "21                         Seton Hall University  1923.0         Teaneck   \n",
       "22                 City College of San Francisco  1927.0   San Francisco   \n",
       "23                       University of Minnesota  1919.0     Minneapolis   \n",
       "24                   East Texas State University  1917.0             NaN   \n",
       "25                   East Texas State University  1924.0             NaN   \n",
       "26                                           NaN  1917.0         Buffalo   \n",
       "27                    Louisiana State University  1920.0             NaN   \n",
       "28                              Canisius College  1925.0     New Orleans   \n",
       "29                               Rice University  1922.0            Edge   \n",
       "...                                          ...     ...             ...   \n",
       "3892                    University of Louisville  1996.0       Baltimore   \n",
       "3893                                         NaN  1997.0       Amarousio   \n",
       "3894                     Oregon State University  1968.0         Oakland   \n",
       "3895                             Duke University  1990.0      Fort Wayne   \n",
       "3896                          University of Utah  1995.0          Vienna   \n",
       "3897                      University of Kentucky  1993.0        Savannah   \n",
       "3898                  Louisiana State University  1994.0        Savannah   \n",
       "3899                         Stanford University  1993.0     Rock Island   \n",
       "3900                         Syracuse University  1996.0         Trenton   \n",
       "3901                          Gonzaga University  1996.0        Portland   \n",
       "3902                                         NaN  1994.0         Sibenik   \n",
       "3903                                         NaN  1991.0          Prague   \n",
       "3904                        University of Kansas  1994.0         Roxbury   \n",
       "3905                 New Mexico State University  1994.0          Douala   \n",
       "3906                      University of Maryland  1997.0       Milwaukee   \n",
       "3907                                         NaN  1997.0             NaN   \n",
       "3908               University of Texas at Austin  1994.0         Hayward   \n",
       "3909                      University of Virginia  1994.0          Monroe   \n",
       "3910                      University of Kentucky  1996.0         Detroit   \n",
       "3911                          University of Iowa  1993.0    Cedar Rapids   \n",
       "3912                   Michigan State University  1993.0         Lansing   \n",
       "3913                    Wichita State University  1994.0        Rockford   \n",
       "3914                                         NaN  1994.0             NaN   \n",
       "3915                    Florida State University  1992.0      Clearwater   \n",
       "3916                       Seton Hall University  1995.0        Brooklyn   \n",
       "3917             South Carolina State University  1969.0        Columbia   \n",
       "3918                          Gonzaga University  1992.0        Portland   \n",
       "3919             University of Nevada, Las Vegas  1996.0  Hendersonville   \n",
       "3920                                         NaN  1994.0      Heidelberg   \n",
       "3921                                         NaN  1997.0          Mostar   \n",
       "\n",
       "                 birth_state  \n",
       "0                        NaN  \n",
       "1                    Indiana  \n",
       "2                        NaN  \n",
       "3                        NaN  \n",
       "4                   Kentucky  \n",
       "5                        NaN  \n",
       "6                      Idaho  \n",
       "7               Pennsylvania  \n",
       "8                 New Jersey  \n",
       "9                    Indiana  \n",
       "10                  Michigan  \n",
       "11                  New York  \n",
       "12                  Oklahoma  \n",
       "13                       NaN  \n",
       "14                  New York  \n",
       "15                 Louisiana  \n",
       "16                     Texas  \n",
       "17                      Ohio  \n",
       "18                  Illinois  \n",
       "19                New Jersey  \n",
       "20                       NaN  \n",
       "21                New Jersey  \n",
       "22                California  \n",
       "23                 Minnesota  \n",
       "24                       NaN  \n",
       "25                       NaN  \n",
       "26                  New York  \n",
       "27                       NaN  \n",
       "28                 Louisiana  \n",
       "29                     Texas  \n",
       "...                      ...  \n",
       "3892                Maryland  \n",
       "3893                  Greece  \n",
       "3894              California  \n",
       "3895                 Indiana  \n",
       "3896                 Austria  \n",
       "3897                 Georgia  \n",
       "3898                 Georgia  \n",
       "3899                Illinois  \n",
       "3900              New Jersey  \n",
       "3901                  Oregon  \n",
       "3902                 Croatia  \n",
       "3903          Czech Republic  \n",
       "3904           Massachusetts  \n",
       "3905                Cameroon  \n",
       "3906               Wisconsin  \n",
       "3907                     NaN  \n",
       "3908              California  \n",
       "3909                New York  \n",
       "3910                Michigan  \n",
       "3911                    Iowa  \n",
       "3912                Michigan  \n",
       "3913                Illinois  \n",
       "3914                     NaN  \n",
       "3915                 Florida  \n",
       "3916                New York  \n",
       "3917          South Carolina  \n",
       "3918                  Oregon  \n",
       "3919               Tennessee  \n",
       "3920                 Germany  \n",
       "3921  Bosnia and Herzegovina  \n",
       "\n",
       "[3922 rows x 7 columns]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.replace({\"Player\":{\"Curly Armstrong\":\"xiao\"}})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>803</th>\n",
       "      <td>Brian Heaney</td>\n",
       "      <td>188.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Acadia University</td>\n",
       "      <td>1946.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3468</th>\n",
       "      <td>Mickell Gladness</td>\n",
       "      <td>211.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>Alabama A&amp;M University</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>Birmingham</td>\n",
       "      <td>Alabama</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1501</th>\n",
       "      <td>Kevin Loder</td>\n",
       "      <td>198.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Alabama State University</td>\n",
       "      <td>1959.0</td>\n",
       "      <td>Cassopolis</td>\n",
       "      <td>Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1368</th>\n",
       "      <td>Major Jones</td>\n",
       "      <td>206.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>Albany State University</td>\n",
       "      <td>1953.0</td>\n",
       "      <td>McGhee</td>\n",
       "      <td>Arkansas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1613</th>\n",
       "      <td>Charles Jones</td>\n",
       "      <td>206.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>Albany State University</td>\n",
       "      <td>1957.0</td>\n",
       "      <td>McGehee</td>\n",
       "      <td>Arkansas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1614</th>\n",
       "      <td>Mark Jones</td>\n",
       "      <td>206.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>Albany State University</td>\n",
       "      <td>1953.0</td>\n",
       "      <td>McGhee</td>\n",
       "      <td>Arkansas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1171</th>\n",
       "      <td>Caldwell Jones</td>\n",
       "      <td>211.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>Albany State University</td>\n",
       "      <td>1950.0</td>\n",
       "      <td>McGehee</td>\n",
       "      <td>Arkansas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1748</th>\n",
       "      <td>Michael Phelps</td>\n",
       "      <td>193.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Alcorn State University</td>\n",
       "      <td>1961.0</td>\n",
       "      <td>Vicksburg</td>\n",
       "      <td>Mississippi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>912</th>\n",
       "      <td>Willie Norwood</td>\n",
       "      <td>201.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>Alcorn State University</td>\n",
       "      <td>1947.0</td>\n",
       "      <td>Carrolton</td>\n",
       "      <td>Mississippi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1454</th>\n",
       "      <td>Larry Smith</td>\n",
       "      <td>203.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>Alcorn State University</td>\n",
       "      <td>1958.0</td>\n",
       "      <td>Rolling Fork</td>\n",
       "      <td>Mississippi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2169</th>\n",
       "      <td>LaBradford Smith</td>\n",
       "      <td>203.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>Alcorn State University</td>\n",
       "      <td>1958.0</td>\n",
       "      <td>Rolling Fork</td>\n",
       "      <td>Mississippi</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>320</th>\n",
       "      <td>Don Asmonga</td>\n",
       "      <td>188.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>Alliance College</td>\n",
       "      <td>1928.0</td>\n",
       "      <td>West Mifflin</td>\n",
       "      <td>Pennsylvania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2067</th>\n",
       "      <td>Mario Elie</td>\n",
       "      <td>196.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>American International College</td>\n",
       "      <td>1963.0</td>\n",
       "      <td>New York</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1015</th>\n",
       "      <td>Kermit Washington</td>\n",
       "      <td>203.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>American University</td>\n",
       "      <td>1951.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>District of Columbia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>Belus Smawley</td>\n",
       "      <td>185.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Appalachian State University</td>\n",
       "      <td>1918.0</td>\n",
       "      <td>Golden Valley</td>\n",
       "      <td>North Carolina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2728</th>\n",
       "      <td>Eddie House</td>\n",
       "      <td>185.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Arizona State University</td>\n",
       "      <td>1978.0</td>\n",
       "      <td>Berkeley</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1118</th>\n",
       "      <td>Rudy White</td>\n",
       "      <td>188.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Arizona State University</td>\n",
       "      <td>1953.0</td>\n",
       "      <td>Silver City</td>\n",
       "      <td>New Mexico</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1093</th>\n",
       "      <td>Lionel Hollins</td>\n",
       "      <td>190.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>Arizona State University</td>\n",
       "      <td>1953.0</td>\n",
       "      <td>Ark City</td>\n",
       "      <td>Kansas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1556</th>\n",
       "      <td>Fat Lever</td>\n",
       "      <td>190.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>Arizona State University</td>\n",
       "      <td>1960.0</td>\n",
       "      <td>Pine Bluff</td>\n",
       "      <td>Arkansas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1632</th>\n",
       "      <td>Byron Scott</td>\n",
       "      <td>190.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Arizona State University</td>\n",
       "      <td>1961.0</td>\n",
       "      <td>Ogden</td>\n",
       "      <td>Utah</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>970</th>\n",
       "      <td>Paul Stovall</td>\n",
       "      <td>193.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>Arizona State University</td>\n",
       "      <td>1948.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>627</th>\n",
       "      <td>Joe Caldwell</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Arizona State University</td>\n",
       "      <td>1941.0</td>\n",
       "      <td>Texas City</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1010</th>\n",
       "      <td>Jim Owens</td>\n",
       "      <td>196.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>Arizona State University</td>\n",
       "      <td>1950.0</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3357</th>\n",
       "      <td>James Harden</td>\n",
       "      <td>196.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>Arizona State University</td>\n",
       "      <td>1989.0</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2382</th>\n",
       "      <td>Mario Bennett</td>\n",
       "      <td>198.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>Arizona State University</td>\n",
       "      <td>1973.0</td>\n",
       "      <td>Denton</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3029</th>\n",
       "      <td>Awvee Storey</td>\n",
       "      <td>198.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>Arizona State University</td>\n",
       "      <td>1977.0</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3634</th>\n",
       "      <td>Carrick Felix</td>\n",
       "      <td>198.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>Arizona State University</td>\n",
       "      <td>1990.0</td>\n",
       "      <td>Las Vegas</td>\n",
       "      <td>Arizona</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>717</th>\n",
       "      <td>Dennis Hamilton</td>\n",
       "      <td>203.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Arizona State University</td>\n",
       "      <td>1944.0</td>\n",
       "      <td>Huntington Beach</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1266</th>\n",
       "      <td>Mark Landsberger</td>\n",
       "      <td>203.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>Arizona State University</td>\n",
       "      <td>1955.0</td>\n",
       "      <td>Minot</td>\n",
       "      <td>North Dakota</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1390</th>\n",
       "      <td>Tony Zeno</td>\n",
       "      <td>203.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Arizona State University</td>\n",
       "      <td>1957.0</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3646</th>\n",
       "      <td>Ognjen Kuzmic</td>\n",
       "      <td>216.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1990.0</td>\n",
       "      <td>Doboj</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3801</th>\n",
       "      <td>Salah Mejri</td>\n",
       "      <td>216.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>Jendouba</td>\n",
       "      <td>Tunisia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3838</th>\n",
       "      <td>Dragan Bender</td>\n",
       "      <td>216.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Capljina</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3882</th>\n",
       "      <td>Thon Maker</td>\n",
       "      <td>216.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>South Sudan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3893</th>\n",
       "      <td>Georgios Papagiannis</td>\n",
       "      <td>216.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Amarousio</td>\n",
       "      <td>Greece</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3921</th>\n",
       "      <td>Ivica Zubac</td>\n",
       "      <td>216.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Mostar</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2112</th>\n",
       "      <td>Stojko Vrankovic</td>\n",
       "      <td>218.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1964.0</td>\n",
       "      <td>Drnis</td>\n",
       "      <td>Croatia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2639</th>\n",
       "      <td>Bruno Sundov</td>\n",
       "      <td>218.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1980.0</td>\n",
       "      <td>Split</td>\n",
       "      <td>Croatia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2770</th>\n",
       "      <td>Jake Tsakalidis</td>\n",
       "      <td>218.0</td>\n",
       "      <td>129.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1979.0</td>\n",
       "      <td>Rustavi</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2787</th>\n",
       "      <td>Primoz Brezec</td>\n",
       "      <td>218.0</td>\n",
       "      <td>114.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1979.0</td>\n",
       "      <td>Postojna</td>\n",
       "      <td>Slovenia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2897</th>\n",
       "      <td>Cezary Trybanski</td>\n",
       "      <td>218.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1979.0</td>\n",
       "      <td>Warsaw</td>\n",
       "      <td>Poland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3044</th>\n",
       "      <td>Martynas Andriuskevicius</td>\n",
       "      <td>218.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>Kaunas</td>\n",
       "      <td>Lithuania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3245</th>\n",
       "      <td>Kosta Perovic</td>\n",
       "      <td>218.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Osijek</td>\n",
       "      <td>Croatia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3267</th>\n",
       "      <td>Alexis Ajinca</td>\n",
       "      <td>218.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1988.0</td>\n",
       "      <td>Saint-Etienne</td>\n",
       "      <td>France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3287</th>\n",
       "      <td>Hamed Haddadi</td>\n",
       "      <td>218.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Ahvaz</td>\n",
       "      <td>Islamic Republic of Iran</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3290</th>\n",
       "      <td>J.J. Hickson</td>\n",
       "      <td>218.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1986.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2432</th>\n",
       "      <td>Arvydas Sabonis*</td>\n",
       "      <td>221.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1964.0</td>\n",
       "      <td>Kaunas</td>\n",
       "      <td>Lithuania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2547</th>\n",
       "      <td>Zydrunas Ilgauskas</td>\n",
       "      <td>221.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1975.0</td>\n",
       "      <td>Kaunas</td>\n",
       "      <td>Lithuania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3023</th>\n",
       "      <td>Ha Seung-Jin</td>\n",
       "      <td>221.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Seoul</td>\n",
       "      <td>Republic of Korea</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3796</th>\n",
       "      <td>Boban Marjanovic</td>\n",
       "      <td>221.0</td>\n",
       "      <td>131.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1988.0</td>\n",
       "      <td>Zajecar</td>\n",
       "      <td>Serbia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3812</th>\n",
       "      <td>Tibor Pleiss</td>\n",
       "      <td>221.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1989.0</td>\n",
       "      <td>Bergisch Gladbach</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3814</th>\n",
       "      <td>Kristaps Porzingis</td>\n",
       "      <td>221.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>Liepaja</td>\n",
       "      <td>Latvia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3822</th>\n",
       "      <td>Walter Tavares</td>\n",
       "      <td>221.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>Maio</td>\n",
       "      <td>Cape Verde</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2969</th>\n",
       "      <td>Slavko Vranes</td>\n",
       "      <td>226.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1983.0</td>\n",
       "      <td>Belgrade</td>\n",
       "      <td>Serbia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3017</th>\n",
       "      <td>Pavel Podkolzin</td>\n",
       "      <td>226.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Novosibirsk</td>\n",
       "      <td>Russia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3018</th>\n",
       "      <td>Peter John</td>\n",
       "      <td>226.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2249</th>\n",
       "      <td>P.J. Brown</td>\n",
       "      <td>229.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1972.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2878</th>\n",
       "      <td>Yao Ming*</td>\n",
       "      <td>229.0</td>\n",
       "      <td>140.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1980.0</td>\n",
       "      <td>Shanghai</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2297</th>\n",
       "      <td>Gheorghe Muresan</td>\n",
       "      <td>231.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1971.0</td>\n",
       "      <td>Triteni</td>\n",
       "      <td>Romania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3922 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Player  Height  Weight  \\\n",
       "803               Brian Heaney   188.0    81.0   \n",
       "3468          Mickell Gladness   211.0    99.0   \n",
       "1501               Kevin Loder   198.0    92.0   \n",
       "1368               Major Jones   206.0   102.0   \n",
       "1613             Charles Jones   206.0    97.0   \n",
       "1614                Mark Jones   206.0   102.0   \n",
       "1171            Caldwell Jones   211.0    98.0   \n",
       "1748            Michael Phelps   193.0    81.0   \n",
       "912             Willie Norwood   201.0    99.0   \n",
       "1454               Larry Smith   203.0    97.0   \n",
       "2169          LaBradford Smith   203.0    97.0   \n",
       "320                Don Asmonga   188.0    83.0   \n",
       "2067                Mario Elie   196.0    95.0   \n",
       "1015         Kermit Washington   203.0   104.0   \n",
       "197              Belus Smawley   185.0    88.0   \n",
       "2728               Eddie House   185.0    81.0   \n",
       "1118                Rudy White   188.0    88.0   \n",
       "1093            Lionel Hollins   190.0    83.0   \n",
       "1556                 Fat Lever   190.0    77.0   \n",
       "1632               Byron Scott   190.0    88.0   \n",
       "970               Paul Stovall   193.0    97.0   \n",
       "627               Joe Caldwell   196.0    88.0   \n",
       "1010                 Jim Owens   196.0    90.0   \n",
       "3357              James Harden   196.0    99.0   \n",
       "2382             Mario Bennett   198.0   106.0   \n",
       "3029              Awvee Storey   198.0   100.0   \n",
       "3634             Carrick Felix   198.0    91.0   \n",
       "717            Dennis Hamilton   203.0    95.0   \n",
       "1266          Mark Landsberger   203.0    97.0   \n",
       "1390                 Tony Zeno   203.0    95.0   \n",
       "...                        ...     ...     ...   \n",
       "3646             Ognjen Kuzmic   216.0   113.0   \n",
       "3801               Salah Mejri   216.0   111.0   \n",
       "3838             Dragan Bender   216.0   102.0   \n",
       "3882                Thon Maker   216.0    97.0   \n",
       "3893      Georgios Papagiannis   216.0   108.0   \n",
       "3921               Ivica Zubac   216.0   120.0   \n",
       "2112          Stojko Vrankovic   218.0   117.0   \n",
       "2639              Bruno Sundov   218.0    99.0   \n",
       "2770           Jake Tsakalidis   218.0   129.0   \n",
       "2787             Primoz Brezec   218.0   114.0   \n",
       "2897          Cezary Trybanski   218.0   108.0   \n",
       "3044  Martynas Andriuskevicius   218.0   108.0   \n",
       "3245             Kosta Perovic   218.0   108.0   \n",
       "3267             Alexis Ajinca   218.0   112.0   \n",
       "3287             Hamed Haddadi   218.0   115.0   \n",
       "3290              J.J. Hickson   218.0   122.0   \n",
       "2432          Arvydas Sabonis*   221.0   126.0   \n",
       "2547        Zydrunas Ilgauskas   221.0   107.0   \n",
       "3023              Ha Seung-Jin   221.0   138.0   \n",
       "3796          Boban Marjanovic   221.0   131.0   \n",
       "3812              Tibor Pleiss   221.0   116.0   \n",
       "3814        Kristaps Porzingis   221.0   108.0   \n",
       "3822            Walter Tavares   221.0   117.0   \n",
       "2969             Slavko Vranes   226.0   124.0   \n",
       "3017           Pavel Podkolzin   226.0   117.0   \n",
       "3018                Peter John   226.0   117.0   \n",
       "2249                P.J. Brown   229.0   106.0   \n",
       "2878                 Yao Ming*   229.0   140.0   \n",
       "2297          Gheorghe Muresan   231.0   137.0   \n",
       "223                        NaN     NaN     NaN   \n",
       "\n",
       "                             collage    born         birth_city  \\\n",
       "803                Acadia University  1946.0                NaN   \n",
       "3468          Alabama A&M University  1986.0         Birmingham   \n",
       "1501        Alabama State University  1959.0         Cassopolis   \n",
       "1368         Albany State University  1953.0             McGhee   \n",
       "1613         Albany State University  1957.0            McGehee   \n",
       "1614         Albany State University  1953.0             McGhee   \n",
       "1171         Albany State University  1950.0            McGehee   \n",
       "1748         Alcorn State University  1961.0          Vicksburg   \n",
       "912          Alcorn State University  1947.0          Carrolton   \n",
       "1454         Alcorn State University  1958.0       Rolling Fork   \n",
       "2169         Alcorn State University  1958.0       Rolling Fork   \n",
       "320                 Alliance College  1928.0       West Mifflin   \n",
       "2067  American International College  1963.0           New York   \n",
       "1015             American University  1951.0         Washington   \n",
       "197     Appalachian State University  1918.0      Golden Valley   \n",
       "2728        Arizona State University  1978.0           Berkeley   \n",
       "1118        Arizona State University  1953.0        Silver City   \n",
       "1093        Arizona State University  1953.0           Ark City   \n",
       "1556        Arizona State University  1960.0         Pine Bluff   \n",
       "1632        Arizona State University  1961.0              Ogden   \n",
       "970         Arizona State University  1948.0                NaN   \n",
       "627         Arizona State University  1941.0         Texas City   \n",
       "1010        Arizona State University  1950.0        Los Angeles   \n",
       "3357        Arizona State University  1989.0        Los Angeles   \n",
       "2382        Arizona State University  1973.0             Denton   \n",
       "3029        Arizona State University  1977.0            Chicago   \n",
       "3634        Arizona State University  1990.0          Las Vegas   \n",
       "717         Arizona State University  1944.0   Huntington Beach   \n",
       "1266        Arizona State University  1955.0              Minot   \n",
       "1390        Arizona State University  1957.0        New Orleans   \n",
       "...                              ...     ...                ...   \n",
       "3646                             NaN  1990.0              Doboj   \n",
       "3801                             NaN  1986.0           Jendouba   \n",
       "3838                             NaN  1997.0           Capljina   \n",
       "3882                             NaN  1997.0        South Sudan   \n",
       "3893                             NaN  1997.0          Amarousio   \n",
       "3921                             NaN  1997.0             Mostar   \n",
       "2112                             NaN  1964.0              Drnis   \n",
       "2639                             NaN  1980.0              Split   \n",
       "2770                             NaN  1979.0            Rustavi   \n",
       "2787                             NaN  1979.0           Postojna   \n",
       "2897                             NaN  1979.0             Warsaw   \n",
       "3044                             NaN  1986.0             Kaunas   \n",
       "3245                             NaN  1985.0             Osijek   \n",
       "3267                             NaN  1988.0      Saint-Etienne   \n",
       "3287                             NaN  1985.0              Ahvaz   \n",
       "3290                             NaN  1986.0                NaN   \n",
       "2432                             NaN  1964.0             Kaunas   \n",
       "2547                             NaN  1975.0             Kaunas   \n",
       "3023                             NaN  1985.0              Seoul   \n",
       "3796                             NaN  1988.0            Zajecar   \n",
       "3812                             NaN  1989.0  Bergisch Gladbach   \n",
       "3814                             NaN  1995.0            Liepaja   \n",
       "3822                             NaN  1992.0               Maio   \n",
       "2969                             NaN  1983.0           Belgrade   \n",
       "3017                             NaN  1985.0        Novosibirsk   \n",
       "3018                             NaN  1985.0                NaN   \n",
       "2249                             NaN  1972.0                NaN   \n",
       "2878                             NaN  1980.0           Shanghai   \n",
       "2297                             NaN  1971.0            Triteni   \n",
       "223                              NaN     NaN                NaN   \n",
       "\n",
       "                   birth_state  \n",
       "803                        NaN  \n",
       "3468                   Alabama  \n",
       "1501                  Michigan  \n",
       "1368                  Arkansas  \n",
       "1613                  Arkansas  \n",
       "1614                  Arkansas  \n",
       "1171                  Arkansas  \n",
       "1748               Mississippi  \n",
       "912                Mississippi  \n",
       "1454               Mississippi  \n",
       "2169               Mississippi  \n",
       "320               Pennsylvania  \n",
       "2067                  New York  \n",
       "1015      District of Columbia  \n",
       "197             North Carolina  \n",
       "2728                California  \n",
       "1118                New Mexico  \n",
       "1093                    Kansas  \n",
       "1556                  Arkansas  \n",
       "1632                      Utah  \n",
       "970                        NaN  \n",
       "627                      Texas  \n",
       "1010                California  \n",
       "3357                California  \n",
       "2382                     Texas  \n",
       "3029                  Illinois  \n",
       "3634                   Arizona  \n",
       "717                 California  \n",
       "1266              North Dakota  \n",
       "1390                 Louisiana  \n",
       "...                        ...  \n",
       "3646    Bosnia and Herzegovina  \n",
       "3801                   Tunisia  \n",
       "3838    Bosnia and Herzegovina  \n",
       "3882                       NaN  \n",
       "3893                    Greece  \n",
       "3921    Bosnia and Herzegovina  \n",
       "2112                   Croatia  \n",
       "2639                   Croatia  \n",
       "2770                   Georgia  \n",
       "2787                  Slovenia  \n",
       "2897                    Poland  \n",
       "3044                 Lithuania  \n",
       "3245                   Croatia  \n",
       "3267                    France  \n",
       "3287  Islamic Republic of Iran  \n",
       "3290                       NaN  \n",
       "2432                 Lithuania  \n",
       "2547                 Lithuania  \n",
       "3023         Republic of Korea  \n",
       "3796                    Serbia  \n",
       "3812                   Germany  \n",
       "3814                    Latvia  \n",
       "3822                Cape Verde  \n",
       "2969                    Serbia  \n",
       "3017                    Russia  \n",
       "3018                       NaN  \n",
       "2249                       NaN  \n",
       "2878                     China  \n",
       "2297                   Romania  \n",
       "223                        NaN  \n",
       "\n",
       "[3922 rows x 7 columns]"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sort_values(by = [\"collage\",\"Height\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Height     160.0\n",
       "Weight      60.0\n",
       "born      1913.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df.head()\n",
    "df.tail()\n",
    "?df.rename()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**数据选取/添加/删除**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>height</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Curly Armstrong</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cliff Barker</td>\n",
       "      <td>188.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leo Barnhorst</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ed Bartels</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ralph Beard</td>\n",
       "      <td>178.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Gene Berce</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Charlie Black</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Nelson Bobb</td>\n",
       "      <td>183.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Jake Bornheimer</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Vince Boryla</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Don Boven</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Harry Boykoff</td>\n",
       "      <td>208.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Joe Bradley</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Bob Brannum</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Carl Braun</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Frankie Brian</td>\n",
       "      <td>185.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Price Brookfield</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Bob Brown</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Jim Browne</td>\n",
       "      <td>208.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Walt Budko</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Jack Burmaster</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Tommy Byrnes</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Bill Calhoun</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Don Carlson</td>\n",
       "      <td>183.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Bob Carpenter</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Jake Carter</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Al Cervi*</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>John Chaney</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Leroy Chollet</td>\n",
       "      <td>188.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Bill Closs</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3892</th>\n",
       "      <td>Chinanu Onuaku</td>\n",
       "      <td>208.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3893</th>\n",
       "      <td>Georgios Papagiannis</td>\n",
       "      <td>216.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3894</th>\n",
       "      <td>Gary Payton</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3895</th>\n",
       "      <td>Marshall Plumlee</td>\n",
       "      <td>211.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3896</th>\n",
       "      <td>Jakob Poeltl</td>\n",
       "      <td>213.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3897</th>\n",
       "      <td>Alex Poythress</td>\n",
       "      <td>201.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3898</th>\n",
       "      <td>Tim Quarterman</td>\n",
       "      <td>198.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3899</th>\n",
       "      <td>Chasson Randle</td>\n",
       "      <td>188.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3900</th>\n",
       "      <td>Malachi Richardson</td>\n",
       "      <td>198.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3901</th>\n",
       "      <td>Domantas Sabonis</td>\n",
       "      <td>211.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3902</th>\n",
       "      <td>Dario Saric</td>\n",
       "      <td>208.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3903</th>\n",
       "      <td>Tomas Satoransky</td>\n",
       "      <td>201.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3904</th>\n",
       "      <td>Wayne Selden</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3905</th>\n",
       "      <td>Pascal Siakam</td>\n",
       "      <td>206.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3906</th>\n",
       "      <td>Diamond Stone</td>\n",
       "      <td>211.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3907</th>\n",
       "      <td>Edy Tavares</td>\n",
       "      <td>211.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3908</th>\n",
       "      <td>Isaiah Taylor</td>\n",
       "      <td>190.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3909</th>\n",
       "      <td>Mike Tobey</td>\n",
       "      <td>213.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3910</th>\n",
       "      <td>Tyler Ulis</td>\n",
       "      <td>178.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3911</th>\n",
       "      <td>Jarrod Uthoff</td>\n",
       "      <td>206.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3912</th>\n",
       "      <td>Denzel Valentine</td>\n",
       "      <td>198.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3913</th>\n",
       "      <td>Fred VanVleet</td>\n",
       "      <td>183.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3914</th>\n",
       "      <td>Taurean Waller-Prince</td>\n",
       "      <td>183.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3915</th>\n",
       "      <td>Okaro White</td>\n",
       "      <td>203.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3916</th>\n",
       "      <td>Isaiah Whitehead</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3917</th>\n",
       "      <td>Troy Williams</td>\n",
       "      <td>198.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3918</th>\n",
       "      <td>Kyle Wiltjer</td>\n",
       "      <td>208.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3919</th>\n",
       "      <td>Stephen Zimmerman</td>\n",
       "      <td>213.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3920</th>\n",
       "      <td>Paul Zipser</td>\n",
       "      <td>203.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3921</th>\n",
       "      <td>Ivica Zubac</td>\n",
       "      <td>216.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3922 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Player  height\n",
       "0           Curly Armstrong   180.0\n",
       "1              Cliff Barker   188.0\n",
       "2             Leo Barnhorst   193.0\n",
       "3                Ed Bartels   196.0\n",
       "4               Ralph Beard   178.0\n",
       "5                Gene Berce   180.0\n",
       "6             Charlie Black   196.0\n",
       "7               Nelson Bobb   183.0\n",
       "8           Jake Bornheimer   196.0\n",
       "9              Vince Boryla   196.0\n",
       "10                Don Boven   193.0\n",
       "11            Harry Boykoff   208.0\n",
       "12              Joe Bradley   190.0\n",
       "13              Bob Brannum   196.0\n",
       "14               Carl Braun   196.0\n",
       "15            Frankie Brian   185.0\n",
       "16         Price Brookfield   193.0\n",
       "17                Bob Brown   193.0\n",
       "18               Jim Browne   208.0\n",
       "19               Walt Budko   196.0\n",
       "20           Jack Burmaster   190.0\n",
       "21             Tommy Byrnes   190.0\n",
       "22             Bill Calhoun   190.0\n",
       "23              Don Carlson   183.0\n",
       "24            Bob Carpenter   196.0\n",
       "25              Jake Carter   193.0\n",
       "26                Al Cervi*   180.0\n",
       "27              John Chaney   190.0\n",
       "28            Leroy Chollet   188.0\n",
       "29               Bill Closs   196.0\n",
       "...                     ...     ...\n",
       "3892         Chinanu Onuaku   208.0\n",
       "3893   Georgios Papagiannis   216.0\n",
       "3894            Gary Payton   193.0\n",
       "3895       Marshall Plumlee   211.0\n",
       "3896           Jakob Poeltl   213.0\n",
       "3897         Alex Poythress   201.0\n",
       "3898         Tim Quarterman   198.0\n",
       "3899         Chasson Randle   188.0\n",
       "3900     Malachi Richardson   198.0\n",
       "3901       Domantas Sabonis   211.0\n",
       "3902            Dario Saric   208.0\n",
       "3903       Tomas Satoransky   201.0\n",
       "3904           Wayne Selden   196.0\n",
       "3905          Pascal Siakam   206.0\n",
       "3906          Diamond Stone   211.0\n",
       "3907            Edy Tavares   211.0\n",
       "3908          Isaiah Taylor   190.0\n",
       "3909             Mike Tobey   213.0\n",
       "3910             Tyler Ulis   178.0\n",
       "3911          Jarrod Uthoff   206.0\n",
       "3912       Denzel Valentine   198.0\n",
       "3913          Fred VanVleet   183.0\n",
       "3914  Taurean Waller-Prince   183.0\n",
       "3915            Okaro White   203.0\n",
       "3916       Isaiah Whitehead   193.0\n",
       "3917          Troy Williams   198.0\n",
       "3918           Kyle Wiltjer   208.0\n",
       "3919      Stephen Zimmerman   213.0\n",
       "3920            Paul Zipser   203.0\n",
       "3921            Ivica Zubac   216.0\n",
       "\n",
       "[3922 rows x 2 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 选择列数据\n",
    "df['Player']\n",
    "df[['Player','height']]\n",
    "df.Player\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 增加一列\n",
    "df[\"class\"] = 1\n",
    "#df['class']\n",
    "# df.class"
   ]
  },
  {
   "cell_type": "raw",
   "metadata": {},
   "source": [
    "条件筛选：\n",
    "height >= 200 或者height <= 170"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Harry Boykoff</td>\n",
       "      <td>208.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>St. John's University</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Jim Browne</td>\n",
       "      <td>208.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1930.0</td>\n",
       "      <td>Midlothian</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Jack Coleman</td>\n",
       "      <td>201.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>University of Louisville</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>Burgin</td>\n",
       "      <td>Kentucky</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Jack Cotton</td>\n",
       "      <td>201.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>University of Wyoming</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>Miles City</td>\n",
       "      <td>Montana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>Normie Glick</td>\n",
       "      <td>201.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>Loyola Marymount University</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>Joe Graboski</td>\n",
       "      <td>201.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1930.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>Alex Groza</td>\n",
       "      <td>201.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1926.0</td>\n",
       "      <td>Martins Ferry</td>\n",
       "      <td>Ohio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>Robert Hahn</td>\n",
       "      <td>208.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>North Carolina State University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>Chick Halbert</td>\n",
       "      <td>206.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>West Texas A&amp;M University</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>Albany</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>Alex Hannum*</td>\n",
       "      <td>201.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>University of Southern California</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>Bob Harris</td>\n",
       "      <td>201.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Oklahoma State University</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Linden</td>\n",
       "      <td>Tennessee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>Bob Harrison</td>\n",
       "      <td>201.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Oklahoma State University</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Linden</td>\n",
       "      <td>Tennessee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>Bill Henry</td>\n",
       "      <td>206.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>Rice University</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>Dallas</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>Kleggie Hermsen</td>\n",
       "      <td>206.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>University of Minnesota</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>Hill City</td>\n",
       "      <td>Minnesota</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>Noble Jorgensen</td>\n",
       "      <td>206.0</td>\n",
       "      <td>103.0</td>\n",
       "      <td>University of Iowa</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>Lee Knorek</td>\n",
       "      <td>201.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>University of Detroit Mercy</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Warsaw</td>\n",
       "      <td>Poland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>Milo Komenich</td>\n",
       "      <td>201.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>University of Wyoming</td>\n",
       "      <td>1920.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>Ron Livingstone</td>\n",
       "      <td>208.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>University of Wyoming</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>Ed Macauley*</td>\n",
       "      <td>203.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>Saint Louis University</td>\n",
       "      <td>1928.0</td>\n",
       "      <td>St. Louis</td>\n",
       "      <td>Missouri</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>John Mahnken</td>\n",
       "      <td>203.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>Georgetown University</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>New Jersey</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>Ed Mikan</td>\n",
       "      <td>203.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>DePaul University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>George Mikan*</td>\n",
       "      <td>208.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>DePaul University</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>Joliet</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>Vern Mikkelsen*</td>\n",
       "      <td>201.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>Hamline University</td>\n",
       "      <td>1928.0</td>\n",
       "      <td>Fresno</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>Al Miksis</td>\n",
       "      <td>201.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Western Illinois University</td>\n",
       "      <td>1928.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>Murray Mitchell</td>\n",
       "      <td>201.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Sam Houston State University</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>Jack Nichols</td>\n",
       "      <td>201.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>University of Washington</td>\n",
       "      <td>1926.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>Jim Nolan</td>\n",
       "      <td>203.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Georgia Institute of Technology</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Macon</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>George Nostrand</td>\n",
       "      <td>203.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>University of Wyoming</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>Uniondale</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>Mike Novak</td>\n",
       "      <td>206.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>Loyola University of Chicago</td>\n",
       "      <td>1915.0</td>\n",
       "      <td>Chicago</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>Don Otten</td>\n",
       "      <td>208.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>Bowling Green State University</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Bellefontaine</td>\n",
       "      <td>Ohio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3872</th>\n",
       "      <td>Brice Johnson</td>\n",
       "      <td>208.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>University of Utah</td>\n",
       "      <td>1979.0</td>\n",
       "      <td>Salt Lake City</td>\n",
       "      <td>Utah</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3874</th>\n",
       "      <td>Derrick Jones</td>\n",
       "      <td>203.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>University of Miami</td>\n",
       "      <td>1990.0</td>\n",
       "      <td>Stone Mountain</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3875</th>\n",
       "      <td>Mindaugas Kuzminskas</td>\n",
       "      <td>206.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1989.0</td>\n",
       "      <td>Vilnius</td>\n",
       "      <td>Lithuania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3876</th>\n",
       "      <td>Skal Labissiere</td>\n",
       "      <td>211.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Port-Au-Prince</td>\n",
       "      <td>Haiti</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3878</th>\n",
       "      <td>Jake Layman</td>\n",
       "      <td>206.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>University of Maryland</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Norwood</td>\n",
       "      <td>Massachusetts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3879</th>\n",
       "      <td>Caris LeVert</td>\n",
       "      <td>201.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>University of Michigan</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Columbus</td>\n",
       "      <td>Ohio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3880</th>\n",
       "      <td>Shawn Long</td>\n",
       "      <td>206.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>University of Louisiana at Lafayette</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Morgan City</td>\n",
       "      <td>Louisiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3882</th>\n",
       "      <td>Thon Maker</td>\n",
       "      <td>216.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>South Sudan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3883</th>\n",
       "      <td>Patrick McCaw</td>\n",
       "      <td>201.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>University of Nevada, Las Vegas</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>St. Louis</td>\n",
       "      <td>Missouri</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3888</th>\n",
       "      <td>Maurice Ndour</td>\n",
       "      <td>206.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>Ohio University</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>Sindia</td>\n",
       "      <td>Senegal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3889</th>\n",
       "      <td>Georges Niang</td>\n",
       "      <td>203.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>Iowa State University</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Lawrence</td>\n",
       "      <td>Massachusetts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3891</th>\n",
       "      <td>Daniel Ochefu</td>\n",
       "      <td>211.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>Villanova University</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Baltimore</td>\n",
       "      <td>Maryland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3892</th>\n",
       "      <td>Chinanu Onuaku</td>\n",
       "      <td>208.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>University of Louisville</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Baltimore</td>\n",
       "      <td>Maryland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3893</th>\n",
       "      <td>Georgios Papagiannis</td>\n",
       "      <td>216.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Amarousio</td>\n",
       "      <td>Greece</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3895</th>\n",
       "      <td>Marshall Plumlee</td>\n",
       "      <td>211.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>Duke University</td>\n",
       "      <td>1990.0</td>\n",
       "      <td>Fort Wayne</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3896</th>\n",
       "      <td>Jakob Poeltl</td>\n",
       "      <td>213.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>University of Utah</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>Vienna</td>\n",
       "      <td>Austria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3897</th>\n",
       "      <td>Alex Poythress</td>\n",
       "      <td>201.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Savannah</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3901</th>\n",
       "      <td>Domantas Sabonis</td>\n",
       "      <td>211.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>Gonzaga University</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Portland</td>\n",
       "      <td>Oregon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3902</th>\n",
       "      <td>Dario Saric</td>\n",
       "      <td>208.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Sibenik</td>\n",
       "      <td>Croatia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3903</th>\n",
       "      <td>Tomas Satoransky</td>\n",
       "      <td>201.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991.0</td>\n",
       "      <td>Prague</td>\n",
       "      <td>Czech Republic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3905</th>\n",
       "      <td>Pascal Siakam</td>\n",
       "      <td>206.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>New Mexico State University</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Douala</td>\n",
       "      <td>Cameroon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3906</th>\n",
       "      <td>Diamond Stone</td>\n",
       "      <td>211.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>University of Maryland</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Milwaukee</td>\n",
       "      <td>Wisconsin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3907</th>\n",
       "      <td>Edy Tavares</td>\n",
       "      <td>211.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3909</th>\n",
       "      <td>Mike Tobey</td>\n",
       "      <td>213.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>University of Virginia</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Monroe</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3911</th>\n",
       "      <td>Jarrod Uthoff</td>\n",
       "      <td>206.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>University of Iowa</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Cedar Rapids</td>\n",
       "      <td>Iowa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3915</th>\n",
       "      <td>Okaro White</td>\n",
       "      <td>203.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Florida State University</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>Clearwater</td>\n",
       "      <td>Florida</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3918</th>\n",
       "      <td>Kyle Wiltjer</td>\n",
       "      <td>208.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>Gonzaga University</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>Portland</td>\n",
       "      <td>Oregon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3919</th>\n",
       "      <td>Stephen Zimmerman</td>\n",
       "      <td>213.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>University of Nevada, Las Vegas</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Hendersonville</td>\n",
       "      <td>Tennessee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3920</th>\n",
       "      <td>Paul Zipser</td>\n",
       "      <td>203.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Heidelberg</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3921</th>\n",
       "      <td>Ivica Zubac</td>\n",
       "      <td>216.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Mostar</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1940 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    Player  Height  Weight  \\\n",
       "11           Harry Boykoff   208.0   102.0   \n",
       "18              Jim Browne   208.0   106.0   \n",
       "31            Jack Coleman   201.0    88.0   \n",
       "34             Jack Cotton   201.0    90.0   \n",
       "63            Normie Glick   201.0    86.0   \n",
       "65            Joe Graboski   201.0    88.0   \n",
       "68              Alex Groza   201.0    98.0   \n",
       "70             Robert Hahn   208.0   108.0   \n",
       "71           Chick Halbert   206.0   102.0   \n",
       "74            Alex Hannum*   201.0    95.0   \n",
       "76              Bob Harris   201.0    88.0   \n",
       "77            Bob Harrison   201.0    88.0   \n",
       "80              Bill Henry   206.0    97.0   \n",
       "82         Kleggie Hermsen   206.0   102.0   \n",
       "94         Noble Jorgensen   206.0   103.0   \n",
       "102             Lee Knorek   201.0    97.0   \n",
       "103          Milo Komenich   201.0    96.0   \n",
       "111        Ron Livingstone   208.0    99.0   \n",
       "114           Ed Macauley*   203.0    83.0   \n",
       "116           John Mahnken   203.0    99.0   \n",
       "128               Ed Mikan   203.0   104.0   \n",
       "129          George Mikan*   208.0   111.0   \n",
       "130        Vern Mikkelsen*   201.0   104.0   \n",
       "131              Al Miksis   201.0    95.0   \n",
       "132        Murray Mitchell   201.0    95.0   \n",
       "137           Jack Nichols   201.0   100.0   \n",
       "140              Jim Nolan   203.0    95.0   \n",
       "142        George Nostrand   203.0    88.0   \n",
       "143             Mike Novak   206.0    99.0   \n",
       "150              Don Otten   208.0   108.0   \n",
       "...                    ...     ...     ...   \n",
       "3872         Brice Johnson   208.0    95.0   \n",
       "3874         Derrick Jones   203.0   100.0   \n",
       "3875  Mindaugas Kuzminskas   206.0    97.0   \n",
       "3876       Skal Labissiere   211.0   102.0   \n",
       "3878           Jake Layman   206.0    95.0   \n",
       "3879          Caris LeVert   201.0    92.0   \n",
       "3880            Shawn Long   206.0   115.0   \n",
       "3882            Thon Maker   216.0    97.0   \n",
       "3883         Patrick McCaw   201.0    83.0   \n",
       "3888         Maurice Ndour   206.0    90.0   \n",
       "3889         Georges Niang   203.0   104.0   \n",
       "3891         Daniel Ochefu   211.0   111.0   \n",
       "3892        Chinanu Onuaku   208.0   111.0   \n",
       "3893  Georgios Papagiannis   216.0   108.0   \n",
       "3895      Marshall Plumlee   211.0   111.0   \n",
       "3896          Jakob Poeltl   213.0   112.0   \n",
       "3897        Alex Poythress   201.0   107.0   \n",
       "3901      Domantas Sabonis   211.0   108.0   \n",
       "3902           Dario Saric   208.0   101.0   \n",
       "3903      Tomas Satoransky   201.0    95.0   \n",
       "3905         Pascal Siakam   206.0   104.0   \n",
       "3906         Diamond Stone   211.0   115.0   \n",
       "3907           Edy Tavares   211.0   115.0   \n",
       "3909            Mike Tobey   213.0   117.0   \n",
       "3911         Jarrod Uthoff   206.0   100.0   \n",
       "3915           Okaro White   203.0    92.0   \n",
       "3918          Kyle Wiltjer   208.0   108.0   \n",
       "3919     Stephen Zimmerman   213.0   108.0   \n",
       "3920           Paul Zipser   203.0    97.0   \n",
       "3921           Ivica Zubac   216.0   120.0   \n",
       "\n",
       "                                   collage    born      birth_city  \\\n",
       "11                   St. John's University  1922.0        Brooklyn   \n",
       "18                                     NaN  1930.0      Midlothian   \n",
       "31                University of Louisville  1924.0          Burgin   \n",
       "34                   University of Wyoming  1924.0      Miles City   \n",
       "63             Loyola Marymount University  1927.0             NaN   \n",
       "65                                     NaN  1930.0             NaN   \n",
       "68                  University of Kentucky  1926.0   Martins Ferry   \n",
       "70         North Carolina State University  1925.0             NaN   \n",
       "71               West Texas A&M University  1919.0          Albany   \n",
       "74       University of Southern California  1923.0     Los Angeles   \n",
       "76               Oklahoma State University  1927.0          Linden   \n",
       "77               Oklahoma State University  1927.0          Linden   \n",
       "80                         Rice University  1924.0          Dallas   \n",
       "82                 University of Minnesota  1923.0       Hill City   \n",
       "94                      University of Iowa  1925.0             NaN   \n",
       "102            University of Detroit Mercy  1921.0          Warsaw   \n",
       "103                  University of Wyoming  1920.0             NaN   \n",
       "111                  University of Wyoming  1925.0             NaN   \n",
       "114                 Saint Louis University  1928.0       St. Louis   \n",
       "116                  Georgetown University  1922.0      New Jersey   \n",
       "128                      DePaul University  1925.0             NaN   \n",
       "129                      DePaul University  1924.0          Joliet   \n",
       "130                     Hamline University  1928.0          Fresno   \n",
       "131            Western Illinois University  1928.0             NaN   \n",
       "132           Sam Houston State University  1923.0             NaN   \n",
       "137               University of Washington  1926.0             NaN   \n",
       "140        Georgia Institute of Technology  1927.0           Macon   \n",
       "142                  University of Wyoming  1924.0       Uniondale   \n",
       "143           Loyola University of Chicago  1915.0         Chicago   \n",
       "150         Bowling Green State University  1921.0   Bellefontaine   \n",
       "...                                    ...     ...             ...   \n",
       "3872                    University of Utah  1979.0  Salt Lake City   \n",
       "3874                   University of Miami  1990.0  Stone Mountain   \n",
       "3875                                   NaN  1989.0         Vilnius   \n",
       "3876                University of Kentucky  1996.0  Port-Au-Prince   \n",
       "3878                University of Maryland  1994.0         Norwood   \n",
       "3879                University of Michigan  1994.0        Columbus   \n",
       "3880  University of Louisiana at Lafayette  1993.0     Morgan City   \n",
       "3882                                   NaN  1997.0     South Sudan   \n",
       "3883       University of Nevada, Las Vegas  1995.0       St. Louis   \n",
       "3888                       Ohio University  1992.0          Sindia   \n",
       "3889                 Iowa State University  1993.0        Lawrence   \n",
       "3891                  Villanova University  1993.0       Baltimore   \n",
       "3892              University of Louisville  1996.0       Baltimore   \n",
       "3893                                   NaN  1997.0       Amarousio   \n",
       "3895                       Duke University  1990.0      Fort Wayne   \n",
       "3896                    University of Utah  1995.0          Vienna   \n",
       "3897                University of Kentucky  1993.0        Savannah   \n",
       "3901                    Gonzaga University  1996.0        Portland   \n",
       "3902                                   NaN  1994.0         Sibenik   \n",
       "3903                                   NaN  1991.0          Prague   \n",
       "3905           New Mexico State University  1994.0          Douala   \n",
       "3906                University of Maryland  1997.0       Milwaukee   \n",
       "3907                                   NaN  1997.0             NaN   \n",
       "3909                University of Virginia  1994.0          Monroe   \n",
       "3911                    University of Iowa  1993.0    Cedar Rapids   \n",
       "3915              Florida State University  1992.0      Clearwater   \n",
       "3918                    Gonzaga University  1992.0        Portland   \n",
       "3919       University of Nevada, Las Vegas  1996.0  Hendersonville   \n",
       "3920                                   NaN  1994.0      Heidelberg   \n",
       "3921                                   NaN  1997.0          Mostar   \n",
       "\n",
       "                 birth_state  \n",
       "11                  New York  \n",
       "18                  Illinois  \n",
       "31                  Kentucky  \n",
       "34                   Montana  \n",
       "63                       NaN  \n",
       "65                       NaN  \n",
       "68                      Ohio  \n",
       "70                       NaN  \n",
       "71                     Texas  \n",
       "74                California  \n",
       "76                 Tennessee  \n",
       "77                 Tennessee  \n",
       "80                     Texas  \n",
       "82                 Minnesota  \n",
       "94                       NaN  \n",
       "102                   Poland  \n",
       "103                      NaN  \n",
       "111                      NaN  \n",
       "114                 Missouri  \n",
       "116               New Jersey  \n",
       "128                      NaN  \n",
       "129                 Illinois  \n",
       "130               California  \n",
       "131                      NaN  \n",
       "132                      NaN  \n",
       "137                      NaN  \n",
       "140                  Georgia  \n",
       "142                 New York  \n",
       "143                 Illinois  \n",
       "150                     Ohio  \n",
       "...                      ...  \n",
       "3872                    Utah  \n",
       "3874                 Georgia  \n",
       "3875               Lithuania  \n",
       "3876                   Haiti  \n",
       "3878           Massachusetts  \n",
       "3879                    Ohio  \n",
       "3880               Louisiana  \n",
       "3882                     NaN  \n",
       "3883                Missouri  \n",
       "3888                 Senegal  \n",
       "3889           Massachusetts  \n",
       "3891                Maryland  \n",
       "3892                Maryland  \n",
       "3893                  Greece  \n",
       "3895                 Indiana  \n",
       "3896                 Austria  \n",
       "3897                 Georgia  \n",
       "3901                  Oregon  \n",
       "3902                 Croatia  \n",
       "3903          Czech Republic  \n",
       "3905                Cameroon  \n",
       "3906               Wisconsin  \n",
       "3907                     NaN  \n",
       "3909                New York  \n",
       "3911                    Iowa  \n",
       "3915                 Florida  \n",
       "3918                  Oregon  \n",
       "3919               Tennessee  \n",
       "3920                 Germany  \n",
       "3921  Bosnia and Herzegovina  \n",
       "\n",
       "[1940 rows x 7 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df[(df['height'] >= 200) | (df['height'] <=170)]\n",
    "df[(df['Height'] >= 200) | (df['Height'] <=170)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 删除\n",
    "del df['class']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>height</th>\n",
       "      <th>weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Curly Armstrong</td>\n",
       "      <td>180.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>Indiana University</td>\n",
       "      <td>1918.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cliff Barker</td>\n",
       "      <td>188.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Yorktown</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leo Barnhorst</td>\n",
       "      <td>193.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ed Bartels</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>North Carolina State University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ralph Beard</td>\n",
       "      <td>178.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Hardinsburg</td>\n",
       "      <td>Kentucky</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Player  height  weight                          collage    born  \\\n",
       "0  Curly Armstrong   180.0    77.0               Indiana University  1918.0   \n",
       "1     Cliff Barker   188.0    83.0           University of Kentucky  1921.0   \n",
       "2    Leo Barnhorst   193.0    86.0         University of Notre Dame  1924.0   \n",
       "3       Ed Bartels   196.0    88.0  North Carolina State University  1925.0   \n",
       "4      Ralph Beard   178.0    79.0           University of Kentucky  1927.0   \n",
       "\n",
       "    birth_city birth_state  \n",
       "0          NaN         NaN  \n",
       "1     Yorktown     Indiana  \n",
       "2          NaN         NaN  \n",
       "3          NaN         NaN  \n",
       "4  Hardinsburg    Kentucky  "
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "height     779122.0\n",
       "weight     371645.0\n",
       "born      7694491.0\n",
       "dtype: float64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.sum(axis = 0)\n",
    "df.sum(axis = 1)\n",
    "df.sum() # 默认是 axis = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "135"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# somethong different\n",
    "import numpy as np \n",
    "a = np.array([[1,2,3,4,5,56],[3,4,5,1,7,3],[29,3,1,6,2,0]])\n",
    "np.sum(a,axis = 1)\n",
    "np.sum(a,axis = 0)\n",
    "np.sum(a) # 全部求和"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(3, 6)"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.shape"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Missing value\n",
    "pandas使用numpy.nan来代表缺失值。缺失值不会被程序计算。处理的方式：\n",
    "1. 删除含有缺失值的行\n",
    "2. 填充缺失值"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       False\n",
       "1       False\n",
       "2       False\n",
       "3       False\n",
       "4       False\n",
       "5       False\n",
       "6       False\n",
       "7       False\n",
       "8       False\n",
       "9       False\n",
       "10      False\n",
       "11      False\n",
       "12      False\n",
       "13      False\n",
       "14      False\n",
       "15      False\n",
       "16      False\n",
       "17      False\n",
       "18      False\n",
       "19      False\n",
       "20      False\n",
       "21      False\n",
       "22      False\n",
       "23      False\n",
       "24      False\n",
       "25      False\n",
       "26      False\n",
       "27      False\n",
       "28      False\n",
       "29      False\n",
       "        ...  \n",
       "3892    False\n",
       "3893    False\n",
       "3894    False\n",
       "3895    False\n",
       "3896    False\n",
       "3897    False\n",
       "3898    False\n",
       "3899    False\n",
       "3900    False\n",
       "3901    False\n",
       "3902    False\n",
       "3903    False\n",
       "3904    False\n",
       "3905    False\n",
       "3906    False\n",
       "3907    False\n",
       "3908    False\n",
       "3909    False\n",
       "3910    False\n",
       "3911    False\n",
       "3912    False\n",
       "3913    False\n",
       "3914    False\n",
       "3915    False\n",
       "3916    False\n",
       "3917    False\n",
       "3918    False\n",
       "3919    False\n",
       "3920    False\n",
       "3921    False\n",
       "Name: Player, Length: 3922, dtype: bool"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 检测缺失值，返回布尔值\n",
    "\n",
    "pd.isnull(df['Player'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>height</th>\n",
       "      <th>weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cliff Barker</td>\n",
       "      <td>188.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Yorktown</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ralph Beard</td>\n",
       "      <td>178.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Hardinsburg</td>\n",
       "      <td>Kentucky</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Charlie Black</td>\n",
       "      <td>196.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>University of Kansas</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Arco</td>\n",
       "      <td>Idaho</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Nelson Bobb</td>\n",
       "      <td>183.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>Temple University</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Pennsylvania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Jake Bornheimer</td>\n",
       "      <td>196.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>Muhlenberg College</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>New Brunswick</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Vince Boryla</td>\n",
       "      <td>196.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>University of Denver</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>East Chicago</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Don Boven</td>\n",
       "      <td>193.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Western Michigan University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>Kalamazoo</td>\n",
       "      <td>Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Harry Boykoff</td>\n",
       "      <td>208.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>St. John's University</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Joe Bradley</td>\n",
       "      <td>190.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Oklahoma State University</td>\n",
       "      <td>1928.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Oklahoma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Carl Braun</td>\n",
       "      <td>196.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Colgate University</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Frankie Brian</td>\n",
       "      <td>185.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Louisiana State University</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>Zachary</td>\n",
       "      <td>Louisiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Price Brookfield</td>\n",
       "      <td>193.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>West Texas A&amp;M University</td>\n",
       "      <td>1920.0</td>\n",
       "      <td>Floydada</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Bob Brown</td>\n",
       "      <td>193.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Miami University</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>Versailles</td>\n",
       "      <td>Ohio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Walt Budko</td>\n",
       "      <td>196.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>Columbia University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>Kearney</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Tommy Byrnes</td>\n",
       "      <td>190.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Seton Hall University</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>Teaneck</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Bill Calhoun</td>\n",
       "      <td>190.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>City College of San Francisco</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Don Carlson</td>\n",
       "      <td>183.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>University of Minnesota</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>Minneapolis</td>\n",
       "      <td>Minnesota</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Leroy Chollet</td>\n",
       "      <td>188.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>Canisius College</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Bill Closs</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Rice University</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>Edge</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Jack Coleman</td>\n",
       "      <td>201.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>University of Louisville</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>Burgin</td>\n",
       "      <td>Kentucky</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Jack Cotton</td>\n",
       "      <td>201.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>University of Wyoming</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>Miles City</td>\n",
       "      <td>Montana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Dillard Crocker</td>\n",
       "      <td>193.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Western Michigan University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>Coffee County</td>\n",
       "      <td>Tennessee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Chink Crossin</td>\n",
       "      <td>185.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>University of Pennsylvania</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>Luzerne</td>\n",
       "      <td>Pennsylvania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Fran Curran</td>\n",
       "      <td>183.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>Sterling</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Bob Davies*</td>\n",
       "      <td>185.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Seton Hall University</td>\n",
       "      <td>1920.0</td>\n",
       "      <td>Harrisburg</td>\n",
       "      <td>Pennsylvania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Hook Dillon</td>\n",
       "      <td>190.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>University of North Carolina</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>Savannah</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Bob Doll</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>University of Colorado</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>Steamboat Springs</td>\n",
       "      <td>Colorado</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Harry Donovan</td>\n",
       "      <td>188.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Muhlenberg College</td>\n",
       "      <td>1926.0</td>\n",
       "      <td>Union City</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Dike Eddleman</td>\n",
       "      <td>190.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>University of Illinois at Urbana-Champaign</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>Centralia</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Gene Englund</td>\n",
       "      <td>196.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>University of Wisconsin</td>\n",
       "      <td>1917.0</td>\n",
       "      <td>Kenosha</td>\n",
       "      <td>Wisconsin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3885</th>\n",
       "      <td>Rodney McGruder</td>\n",
       "      <td>193.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Kansas State University</td>\n",
       "      <td>1991.0</td>\n",
       "      <td>Landover</td>\n",
       "      <td>Maryland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3886</th>\n",
       "      <td>Dejounte Murray</td>\n",
       "      <td>196.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>University of Washington</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Seattle</td>\n",
       "      <td>Washington</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3887</th>\n",
       "      <td>Jamal Murray</td>\n",
       "      <td>193.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Kitchener</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3888</th>\n",
       "      <td>Maurice Ndour</td>\n",
       "      <td>206.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>Ohio University</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>Sindia</td>\n",
       "      <td>Senegal</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3889</th>\n",
       "      <td>Georges Niang</td>\n",
       "      <td>203.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>Iowa State University</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Lawrence</td>\n",
       "      <td>Massachusetts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3890</th>\n",
       "      <td>David Nwaba</td>\n",
       "      <td>193.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>California Polytechnic State University, San L...</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3891</th>\n",
       "      <td>Daniel Ochefu</td>\n",
       "      <td>211.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>Villanova University</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Baltimore</td>\n",
       "      <td>Maryland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3892</th>\n",
       "      <td>Chinanu Onuaku</td>\n",
       "      <td>208.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>University of Louisville</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Baltimore</td>\n",
       "      <td>Maryland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3894</th>\n",
       "      <td>Gary Payton</td>\n",
       "      <td>193.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Oregon State University</td>\n",
       "      <td>1968.0</td>\n",
       "      <td>Oakland</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3895</th>\n",
       "      <td>Marshall Plumlee</td>\n",
       "      <td>211.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>Duke University</td>\n",
       "      <td>1990.0</td>\n",
       "      <td>Fort Wayne</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3896</th>\n",
       "      <td>Jakob Poeltl</td>\n",
       "      <td>213.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>University of Utah</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>Vienna</td>\n",
       "      <td>Austria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3897</th>\n",
       "      <td>Alex Poythress</td>\n",
       "      <td>201.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Savannah</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3898</th>\n",
       "      <td>Tim Quarterman</td>\n",
       "      <td>198.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Louisiana State University</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Savannah</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3899</th>\n",
       "      <td>Chasson Randle</td>\n",
       "      <td>188.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>Stanford University</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Rock Island</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3900</th>\n",
       "      <td>Malachi Richardson</td>\n",
       "      <td>198.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Syracuse University</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Trenton</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3901</th>\n",
       "      <td>Domantas Sabonis</td>\n",
       "      <td>211.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>Gonzaga University</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Portland</td>\n",
       "      <td>Oregon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3904</th>\n",
       "      <td>Wayne Selden</td>\n",
       "      <td>196.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>University of Kansas</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Roxbury</td>\n",
       "      <td>Massachusetts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3905</th>\n",
       "      <td>Pascal Siakam</td>\n",
       "      <td>206.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>New Mexico State University</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Douala</td>\n",
       "      <td>Cameroon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3906</th>\n",
       "      <td>Diamond Stone</td>\n",
       "      <td>211.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>University of Maryland</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Milwaukee</td>\n",
       "      <td>Wisconsin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3908</th>\n",
       "      <td>Isaiah Taylor</td>\n",
       "      <td>190.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>University of Texas at Austin</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Hayward</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3909</th>\n",
       "      <td>Mike Tobey</td>\n",
       "      <td>213.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>University of Virginia</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Monroe</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3910</th>\n",
       "      <td>Tyler Ulis</td>\n",
       "      <td>178.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Detroit</td>\n",
       "      <td>Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3911</th>\n",
       "      <td>Jarrod Uthoff</td>\n",
       "      <td>206.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>University of Iowa</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Cedar Rapids</td>\n",
       "      <td>Iowa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3912</th>\n",
       "      <td>Denzel Valentine</td>\n",
       "      <td>198.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Michigan State University</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Lansing</td>\n",
       "      <td>Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3913</th>\n",
       "      <td>Fred VanVleet</td>\n",
       "      <td>183.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Wichita State University</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Rockford</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3915</th>\n",
       "      <td>Okaro White</td>\n",
       "      <td>203.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Florida State University</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>Clearwater</td>\n",
       "      <td>Florida</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3916</th>\n",
       "      <td>Isaiah Whitehead</td>\n",
       "      <td>193.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Seton Hall University</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3917</th>\n",
       "      <td>Troy Williams</td>\n",
       "      <td>198.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>South Carolina State University</td>\n",
       "      <td>1969.0</td>\n",
       "      <td>Columbia</td>\n",
       "      <td>South Carolina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3918</th>\n",
       "      <td>Kyle Wiltjer</td>\n",
       "      <td>208.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>Gonzaga University</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>Portland</td>\n",
       "      <td>Oregon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3919</th>\n",
       "      <td>Stephen Zimmerman</td>\n",
       "      <td>213.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>University of Nevada, Las Vegas</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Hendersonville</td>\n",
       "      <td>Tennessee</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3189 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Player  height  weight  \\\n",
       "1           Cliff Barker   188.0    83.0   \n",
       "4            Ralph Beard   178.0    79.0   \n",
       "6          Charlie Black   196.0    90.0   \n",
       "7            Nelson Bobb   183.0    77.0   \n",
       "8        Jake Bornheimer   196.0    90.0   \n",
       "9           Vince Boryla   196.0    95.0   \n",
       "10             Don Boven   193.0    95.0   \n",
       "11         Harry Boykoff   208.0   102.0   \n",
       "12           Joe Bradley   190.0    79.0   \n",
       "14            Carl Braun   196.0    81.0   \n",
       "15         Frankie Brian   185.0    81.0   \n",
       "16      Price Brookfield   193.0    83.0   \n",
       "17             Bob Brown   193.0    92.0   \n",
       "19            Walt Budko   196.0    99.0   \n",
       "21          Tommy Byrnes   190.0    79.0   \n",
       "22          Bill Calhoun   190.0    81.0   \n",
       "23           Don Carlson   183.0    77.0   \n",
       "28         Leroy Chollet   188.0    86.0   \n",
       "29            Bill Closs   196.0    88.0   \n",
       "31          Jack Coleman   201.0    88.0   \n",
       "34           Jack Cotton   201.0    90.0   \n",
       "35       Dillard Crocker   193.0    92.0   \n",
       "36         Chink Crossin   185.0    74.0   \n",
       "37           Fran Curran   183.0    79.0   \n",
       "39           Bob Davies*   185.0    79.0   \n",
       "40           Hook Dillon   190.0    81.0   \n",
       "43              Bob Doll   196.0    88.0   \n",
       "44         Harry Donovan   188.0    81.0   \n",
       "46         Dike Eddleman   190.0    85.0   \n",
       "47          Gene Englund   196.0    92.0   \n",
       "...                  ...     ...     ...   \n",
       "3885     Rodney McGruder   193.0    92.0   \n",
       "3886     Dejounte Murray   196.0    77.0   \n",
       "3887        Jamal Murray   193.0    93.0   \n",
       "3888       Maurice Ndour   206.0    90.0   \n",
       "3889       Georges Niang   203.0   104.0   \n",
       "3890         David Nwaba   193.0    94.0   \n",
       "3891       Daniel Ochefu   211.0   111.0   \n",
       "3892      Chinanu Onuaku   208.0   111.0   \n",
       "3894         Gary Payton   193.0    81.0   \n",
       "3895    Marshall Plumlee   211.0   111.0   \n",
       "3896        Jakob Poeltl   213.0   112.0   \n",
       "3897      Alex Poythress   201.0   107.0   \n",
       "3898      Tim Quarterman   198.0    88.0   \n",
       "3899      Chasson Randle   188.0    83.0   \n",
       "3900  Malachi Richardson   198.0    92.0   \n",
       "3901    Domantas Sabonis   211.0   108.0   \n",
       "3904        Wayne Selden   196.0   104.0   \n",
       "3905       Pascal Siakam   206.0   104.0   \n",
       "3906       Diamond Stone   211.0   115.0   \n",
       "3908       Isaiah Taylor   190.0    77.0   \n",
       "3909          Mike Tobey   213.0   117.0   \n",
       "3910          Tyler Ulis   178.0    68.0   \n",
       "3911       Jarrod Uthoff   206.0   100.0   \n",
       "3912    Denzel Valentine   198.0    96.0   \n",
       "3913       Fred VanVleet   183.0    88.0   \n",
       "3915         Okaro White   203.0    92.0   \n",
       "3916    Isaiah Whitehead   193.0    96.0   \n",
       "3917       Troy Williams   198.0    97.0   \n",
       "3918        Kyle Wiltjer   208.0   108.0   \n",
       "3919   Stephen Zimmerman   213.0   108.0   \n",
       "\n",
       "                                                collage    born  \\\n",
       "1                                University of Kentucky  1921.0   \n",
       "4                                University of Kentucky  1927.0   \n",
       "6                                  University of Kansas  1921.0   \n",
       "7                                     Temple University  1924.0   \n",
       "8                                    Muhlenberg College  1927.0   \n",
       "9                                  University of Denver  1927.0   \n",
       "10                          Western Michigan University  1925.0   \n",
       "11                                St. John's University  1922.0   \n",
       "12                            Oklahoma State University  1928.0   \n",
       "14                                   Colgate University  1927.0   \n",
       "15                           Louisiana State University  1923.0   \n",
       "16                            West Texas A&M University  1920.0   \n",
       "17                                     Miami University  1923.0   \n",
       "19                                  Columbia University  1925.0   \n",
       "21                                Seton Hall University  1923.0   \n",
       "22                        City College of San Francisco  1927.0   \n",
       "23                              University of Minnesota  1919.0   \n",
       "28                                     Canisius College  1925.0   \n",
       "29                                      Rice University  1922.0   \n",
       "31                             University of Louisville  1924.0   \n",
       "34                                University of Wyoming  1924.0   \n",
       "35                          Western Michigan University  1925.0   \n",
       "36                           University of Pennsylvania  1923.0   \n",
       "37                             University of Notre Dame  1922.0   \n",
       "39                                Seton Hall University  1920.0   \n",
       "40                         University of North Carolina  1924.0   \n",
       "43                               University of Colorado  1919.0   \n",
       "44                                   Muhlenberg College  1926.0   \n",
       "46           University of Illinois at Urbana-Champaign  1922.0   \n",
       "47                              University of Wisconsin  1917.0   \n",
       "...                                                 ...     ...   \n",
       "3885                            Kansas State University  1991.0   \n",
       "3886                           University of Washington  1996.0   \n",
       "3887                             University of Kentucky  1997.0   \n",
       "3888                                    Ohio University  1992.0   \n",
       "3889                              Iowa State University  1993.0   \n",
       "3890  California Polytechnic State University, San L...  1993.0   \n",
       "3891                               Villanova University  1993.0   \n",
       "3892                           University of Louisville  1996.0   \n",
       "3894                            Oregon State University  1968.0   \n",
       "3895                                    Duke University  1990.0   \n",
       "3896                                 University of Utah  1995.0   \n",
       "3897                             University of Kentucky  1993.0   \n",
       "3898                         Louisiana State University  1994.0   \n",
       "3899                                Stanford University  1993.0   \n",
       "3900                                Syracuse University  1996.0   \n",
       "3901                                 Gonzaga University  1996.0   \n",
       "3904                               University of Kansas  1994.0   \n",
       "3905                        New Mexico State University  1994.0   \n",
       "3906                             University of Maryland  1997.0   \n",
       "3908                      University of Texas at Austin  1994.0   \n",
       "3909                             University of Virginia  1994.0   \n",
       "3910                             University of Kentucky  1996.0   \n",
       "3911                                 University of Iowa  1993.0   \n",
       "3912                          Michigan State University  1993.0   \n",
       "3913                           Wichita State University  1994.0   \n",
       "3915                           Florida State University  1992.0   \n",
       "3916                              Seton Hall University  1995.0   \n",
       "3917                    South Carolina State University  1969.0   \n",
       "3918                                 Gonzaga University  1992.0   \n",
       "3919                    University of Nevada, Las Vegas  1996.0   \n",
       "\n",
       "             birth_city     birth_state  \n",
       "1              Yorktown         Indiana  \n",
       "4           Hardinsburg        Kentucky  \n",
       "6                  Arco           Idaho  \n",
       "7          Philadelphia    Pennsylvania  \n",
       "8         New Brunswick      New Jersey  \n",
       "9          East Chicago         Indiana  \n",
       "10            Kalamazoo        Michigan  \n",
       "11             Brooklyn        New York  \n",
       "12           Washington        Oklahoma  \n",
       "14             Brooklyn        New York  \n",
       "15              Zachary       Louisiana  \n",
       "16             Floydada           Texas  \n",
       "17           Versailles            Ohio  \n",
       "19              Kearney      New Jersey  \n",
       "21              Teaneck      New Jersey  \n",
       "22        San Francisco      California  \n",
       "23          Minneapolis       Minnesota  \n",
       "28          New Orleans       Louisiana  \n",
       "29                 Edge           Texas  \n",
       "31               Burgin        Kentucky  \n",
       "34           Miles City         Montana  \n",
       "35        Coffee County       Tennessee  \n",
       "36              Luzerne    Pennsylvania  \n",
       "37             Sterling        Illinois  \n",
       "39           Harrisburg    Pennsylvania  \n",
       "40             Savannah         Georgia  \n",
       "43    Steamboat Springs        Colorado  \n",
       "44           Union City      New Jersey  \n",
       "46            Centralia        Illinois  \n",
       "47              Kenosha       Wisconsin  \n",
       "...                 ...             ...  \n",
       "3885           Landover        Maryland  \n",
       "3886            Seattle      Washington  \n",
       "3887          Kitchener          Canada  \n",
       "3888             Sindia         Senegal  \n",
       "3889           Lawrence   Massachusetts  \n",
       "3890        Los Angeles      California  \n",
       "3891          Baltimore        Maryland  \n",
       "3892          Baltimore        Maryland  \n",
       "3894            Oakland      California  \n",
       "3895         Fort Wayne         Indiana  \n",
       "3896             Vienna         Austria  \n",
       "3897           Savannah         Georgia  \n",
       "3898           Savannah         Georgia  \n",
       "3899        Rock Island        Illinois  \n",
       "3900            Trenton      New Jersey  \n",
       "3901           Portland          Oregon  \n",
       "3904            Roxbury   Massachusetts  \n",
       "3905             Douala        Cameroon  \n",
       "3906          Milwaukee       Wisconsin  \n",
       "3908            Hayward      California  \n",
       "3909             Monroe        New York  \n",
       "3910            Detroit        Michigan  \n",
       "3911       Cedar Rapids            Iowa  \n",
       "3912            Lansing        Michigan  \n",
       "3913           Rockford        Illinois  \n",
       "3915         Clearwater         Florida  \n",
       "3916           Brooklyn        New York  \n",
       "3917           Columbia  South Carolina  \n",
       "3918           Portland          Oregon  \n",
       "3919     Hendersonville       Tennessee  \n",
       "\n",
       "[3189 rows x 7 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 删除缺失值的行\n",
    "df.dropna(axis=0, how='any', thresh=None, subset=None, inplace=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# 填充缺失值\n",
    "df.fillna(value=None, method=None, axis=None, inplace=False, limit=None, downcast=None, **kwargs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "?df.fillna"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 文本数据\n",
    "dataframe与series中经常有文本格式的数据存在，pandas提供了良好的工具用来处理这些文本"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3    Aaba \n",
       "4     Baca\n",
       "dtype: object"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s = pd.Series(['A', 'B', 'C', 'Aaba ', ' Baca', 'CABA ', 'dog', 'cat'])\n",
    "s.str.strip()\n",
    "s.str.upper()\n",
    "s[s.str.strip().str.endswith(\"a\")]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "一个很常用的场景就是当你的index或者column名称前后包含了空格的时候，你可以用str的方法剔除这些空格，从而避免不必要的麻烦"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "a = {\"name \":[\"xiaoming\",\"xiaohong\",\"xiaogang\"],\" age\":[12,13,14]}\n",
    "test = pd.DataFrame(data = a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>12</td>\n",
       "      <td>xiaoming</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>13</td>\n",
       "      <td>xiaohong</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>14</td>\n",
       "      <td>xiaogang</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    age     name \n",
       "0    12  xiaoming\n",
       "1    13  xiaohong\n",
       "2    14  xiaogang"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "test['age'] # ERROR\n",
    "test.columns = test.columns.str.strip()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0    12\n",
       "1    13\n",
       "2    14\n",
       "Name: age, dtype: int64"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test['age'] "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Splitting and Replacing String\n",
    "split方法用于根据某个分隔符对字符进行分割，返回一个列表"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0             Curly Armstrong\n",
       "1                Cliff Barker\n",
       "2               Leo Barnhorst\n",
       "3                  Ed Bartels\n",
       "4                 Ralph Beard\n",
       "5                  Gene Berce\n",
       "6               Charlie Black\n",
       "7                 Nelson Bobb\n",
       "8             Jake Bornheimer\n",
       "9                Vince Boryla\n",
       "10                  Don Boven\n",
       "11              Harry Boykoff\n",
       "12                Joe Bradley\n",
       "13                Bob Brannum\n",
       "14                 Carl Braun\n",
       "15              Frankie Brian\n",
       "16           Price Brookfield\n",
       "17                  Bob Brown\n",
       "18                 Jim Browne\n",
       "19                 Walt Budko\n",
       "20             Jack Burmaster\n",
       "21               Tommy Byrnes\n",
       "22               Bill Calhoun\n",
       "23                Don Carlson\n",
       "24              Bob Carpenter\n",
       "25                Jake Carter\n",
       "26                  Al Cervi*\n",
       "27                John Chaney\n",
       "28              Leroy Chollet\n",
       "29                 Bill Closs\n",
       "                ...          \n",
       "3892           Chinanu Onuaku\n",
       "3893     Georgios Papagiannis\n",
       "3894              Gary Payton\n",
       "3895         Marshall Plumlee\n",
       "3896             Jakob Poeltl\n",
       "3897           Alex Poythress\n",
       "3898           Tim Quarterman\n",
       "3899           Chasson Randle\n",
       "3900       Malachi Richardson\n",
       "3901         Domantas Sabonis\n",
       "3902              Dario Saric\n",
       "3903         Tomas Satoransky\n",
       "3904             Wayne Selden\n",
       "3905            Pascal Siakam\n",
       "3906            Diamond Stone\n",
       "3907              Edy Tavares\n",
       "3908            Isaiah Taylor\n",
       "3909               Mike Tobey\n",
       "3910               Tyler Ulis\n",
       "3911            Jarrod Uthoff\n",
       "3912         Denzel Valentine\n",
       "3913            Fred VanVleet\n",
       "3914    Taurean Waller-Prince\n",
       "3915              Okaro White\n",
       "3916         Isaiah Whitehead\n",
       "3917            Troy Williams\n",
       "3918             Kyle Wiltjer\n",
       "3919        Stephen Zimmerman\n",
       "3920              Paul Zipser\n",
       "3921              Ivica Zubac\n",
       "Name: Player, Length: 3922, dtype: object"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Player']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0             [Curly, Armstrong]\n",
       "1                [Cliff, Barker]\n",
       "2               [Leo, Barnhorst]\n",
       "3                  [Ed, Bartels]\n",
       "4                 [Ralph, Beard]\n",
       "5                  [Gene, Berce]\n",
       "6               [Charlie, Black]\n",
       "7                 [Nelson, Bobb]\n",
       "8             [Jake, Bornheimer]\n",
       "9                [Vince, Boryla]\n",
       "10                  [Don, Boven]\n",
       "11              [Harry, Boykoff]\n",
       "12                [Joe, Bradley]\n",
       "13                [Bob, Brannum]\n",
       "14                 [Carl, Braun]\n",
       "15              [Frankie, Brian]\n",
       "16           [Price, Brookfield]\n",
       "17                  [Bob, Brown]\n",
       "18                 [Jim, Browne]\n",
       "19                 [Walt, Budko]\n",
       "20             [Jack, Burmaster]\n",
       "21               [Tommy, Byrnes]\n",
       "22               [Bill, Calhoun]\n",
       "23                [Don, Carlson]\n",
       "24              [Bob, Carpenter]\n",
       "25                [Jake, Carter]\n",
       "26                  [Al, Cervi*]\n",
       "27                [John, Chaney]\n",
       "28              [Leroy, Chollet]\n",
       "29                 [Bill, Closs]\n",
       "                  ...           \n",
       "3892           [Chinanu, Onuaku]\n",
       "3893     [Georgios, Papagiannis]\n",
       "3894              [Gary, Payton]\n",
       "3895         [Marshall, Plumlee]\n",
       "3896             [Jakob, Poeltl]\n",
       "3897           [Alex, Poythress]\n",
       "3898           [Tim, Quarterman]\n",
       "3899           [Chasson, Randle]\n",
       "3900       [Malachi, Richardson]\n",
       "3901         [Domantas, Sabonis]\n",
       "3902              [Dario, Saric]\n",
       "3903         [Tomas, Satoransky]\n",
       "3904             [Wayne, Selden]\n",
       "3905            [Pascal, Siakam]\n",
       "3906            [Diamond, Stone]\n",
       "3907              [Edy, Tavares]\n",
       "3908            [Isaiah, Taylor]\n",
       "3909               [Mike, Tobey]\n",
       "3910               [Tyler, Ulis]\n",
       "3911            [Jarrod, Uthoff]\n",
       "3912         [Denzel, Valentine]\n",
       "3913            [Fred, VanVleet]\n",
       "3914    [Taurean, Waller-Prince]\n",
       "3915              [Okaro, White]\n",
       "3916         [Isaiah, Whitehead]\n",
       "3917            [Troy, Williams]\n",
       "3918             [Kyle, Wiltjer]\n",
       "3919        [Stephen, Zimmerman]\n",
       "3920              [Paul, Zipser]\n",
       "3921              [Ivica, Zubac]\n",
       "Name: Player, Length: 3922, dtype: object"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Player'].str.split(\" \") # 姓和名进行分割"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0           Armstrong\n",
       "1              Barker\n",
       "2           Barnhorst\n",
       "3             Bartels\n",
       "4               Beard\n",
       "5               Berce\n",
       "6               Black\n",
       "7                Bobb\n",
       "8          Bornheimer\n",
       "9              Boryla\n",
       "10              Boven\n",
       "11            Boykoff\n",
       "12            Bradley\n",
       "13            Brannum\n",
       "14              Braun\n",
       "15              Brian\n",
       "16         Brookfield\n",
       "17              Brown\n",
       "18             Browne\n",
       "19              Budko\n",
       "20          Burmaster\n",
       "21             Byrnes\n",
       "22            Calhoun\n",
       "23            Carlson\n",
       "24          Carpenter\n",
       "25             Carter\n",
       "26             Cervi*\n",
       "27             Chaney\n",
       "28            Chollet\n",
       "29              Closs\n",
       "            ...      \n",
       "3892           Onuaku\n",
       "3893      Papagiannis\n",
       "3894           Payton\n",
       "3895          Plumlee\n",
       "3896           Poeltl\n",
       "3897        Poythress\n",
       "3898       Quarterman\n",
       "3899           Randle\n",
       "3900       Richardson\n",
       "3901          Sabonis\n",
       "3902            Saric\n",
       "3903       Satoransky\n",
       "3904           Selden\n",
       "3905           Siakam\n",
       "3906            Stone\n",
       "3907          Tavares\n",
       "3908           Taylor\n",
       "3909            Tobey\n",
       "3910             Ulis\n",
       "3911           Uthoff\n",
       "3912        Valentine\n",
       "3913         VanVleet\n",
       "3914    Waller-Prince\n",
       "3915            White\n",
       "3916        Whitehead\n",
       "3917         Williams\n",
       "3918          Wiltjer\n",
       "3919        Zimmerman\n",
       "3920           Zipser\n",
       "3921            Zubac\n",
       "Name: Player, Length: 3922, dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 使用get方法获取指定位置的元素\n",
    "df['Player'].str.split(\" \").str.get(1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>0</th>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Curly</td>\n",
       "      <td>Armstrong</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cliff</td>\n",
       "      <td>Barker</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leo</td>\n",
       "      <td>Barnhorst</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ed</td>\n",
       "      <td>Bartels</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ralph</td>\n",
       "      <td>Beard</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Gene</td>\n",
       "      <td>Berce</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Charlie</td>\n",
       "      <td>Black</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Nelson</td>\n",
       "      <td>Bobb</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Jake</td>\n",
       "      <td>Bornheimer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Vince</td>\n",
       "      <td>Boryla</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Don</td>\n",
       "      <td>Boven</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Harry</td>\n",
       "      <td>Boykoff</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Joe</td>\n",
       "      <td>Bradley</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Bob</td>\n",
       "      <td>Brannum</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Carl</td>\n",
       "      <td>Braun</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Frankie</td>\n",
       "      <td>Brian</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Price</td>\n",
       "      <td>Brookfield</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Bob</td>\n",
       "      <td>Brown</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Jim</td>\n",
       "      <td>Browne</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Walt</td>\n",
       "      <td>Budko</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Jack</td>\n",
       "      <td>Burmaster</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Tommy</td>\n",
       "      <td>Byrnes</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Bill</td>\n",
       "      <td>Calhoun</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Don</td>\n",
       "      <td>Carlson</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Bob</td>\n",
       "      <td>Carpenter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Jake</td>\n",
       "      <td>Carter</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Al</td>\n",
       "      <td>Cervi*</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>John</td>\n",
       "      <td>Chaney</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Leroy</td>\n",
       "      <td>Chollet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Bill</td>\n",
       "      <td>Closs</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3892</th>\n",
       "      <td>Chinanu</td>\n",
       "      <td>Onuaku</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3893</th>\n",
       "      <td>Georgios</td>\n",
       "      <td>Papagiannis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3894</th>\n",
       "      <td>Gary</td>\n",
       "      <td>Payton</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3895</th>\n",
       "      <td>Marshall</td>\n",
       "      <td>Plumlee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3896</th>\n",
       "      <td>Jakob</td>\n",
       "      <td>Poeltl</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3897</th>\n",
       "      <td>Alex</td>\n",
       "      <td>Poythress</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3898</th>\n",
       "      <td>Tim</td>\n",
       "      <td>Quarterman</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3899</th>\n",
       "      <td>Chasson</td>\n",
       "      <td>Randle</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3900</th>\n",
       "      <td>Malachi</td>\n",
       "      <td>Richardson</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3901</th>\n",
       "      <td>Domantas</td>\n",
       "      <td>Sabonis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3902</th>\n",
       "      <td>Dario</td>\n",
       "      <td>Saric</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3903</th>\n",
       "      <td>Tomas</td>\n",
       "      <td>Satoransky</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3904</th>\n",
       "      <td>Wayne</td>\n",
       "      <td>Selden</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3905</th>\n",
       "      <td>Pascal</td>\n",
       "      <td>Siakam</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3906</th>\n",
       "      <td>Diamond</td>\n",
       "      <td>Stone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3907</th>\n",
       "      <td>Edy</td>\n",
       "      <td>Tavares</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3908</th>\n",
       "      <td>Isaiah</td>\n",
       "      <td>Taylor</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3909</th>\n",
       "      <td>Mike</td>\n",
       "      <td>Tobey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3910</th>\n",
       "      <td>Tyler</td>\n",
       "      <td>Ulis</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3911</th>\n",
       "      <td>Jarrod</td>\n",
       "      <td>Uthoff</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3912</th>\n",
       "      <td>Denzel</td>\n",
       "      <td>Valentine</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3913</th>\n",
       "      <td>Fred</td>\n",
       "      <td>VanVleet</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3914</th>\n",
       "      <td>Taurean</td>\n",
       "      <td>Waller-Prince</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3915</th>\n",
       "      <td>Okaro</td>\n",
       "      <td>White</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3916</th>\n",
       "      <td>Isaiah</td>\n",
       "      <td>Whitehead</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3917</th>\n",
       "      <td>Troy</td>\n",
       "      <td>Williams</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3918</th>\n",
       "      <td>Kyle</td>\n",
       "      <td>Wiltjer</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3919</th>\n",
       "      <td>Stephen</td>\n",
       "      <td>Zimmerman</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3920</th>\n",
       "      <td>Paul</td>\n",
       "      <td>Zipser</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3921</th>\n",
       "      <td>Ivica</td>\n",
       "      <td>Zubac</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3922 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             0              1\n",
       "0        Curly      Armstrong\n",
       "1        Cliff         Barker\n",
       "2          Leo      Barnhorst\n",
       "3           Ed        Bartels\n",
       "4        Ralph          Beard\n",
       "5         Gene          Berce\n",
       "6      Charlie          Black\n",
       "7       Nelson           Bobb\n",
       "8         Jake     Bornheimer\n",
       "9        Vince         Boryla\n",
       "10         Don          Boven\n",
       "11       Harry        Boykoff\n",
       "12         Joe        Bradley\n",
       "13         Bob        Brannum\n",
       "14        Carl          Braun\n",
       "15     Frankie          Brian\n",
       "16       Price     Brookfield\n",
       "17         Bob          Brown\n",
       "18         Jim         Browne\n",
       "19        Walt          Budko\n",
       "20        Jack      Burmaster\n",
       "21       Tommy         Byrnes\n",
       "22        Bill        Calhoun\n",
       "23         Don        Carlson\n",
       "24         Bob      Carpenter\n",
       "25        Jake         Carter\n",
       "26          Al         Cervi*\n",
       "27        John         Chaney\n",
       "28       Leroy        Chollet\n",
       "29        Bill          Closs\n",
       "...        ...            ...\n",
       "3892   Chinanu         Onuaku\n",
       "3893  Georgios    Papagiannis\n",
       "3894      Gary         Payton\n",
       "3895  Marshall        Plumlee\n",
       "3896     Jakob         Poeltl\n",
       "3897      Alex      Poythress\n",
       "3898       Tim     Quarterman\n",
       "3899   Chasson         Randle\n",
       "3900   Malachi     Richardson\n",
       "3901  Domantas        Sabonis\n",
       "3902     Dario          Saric\n",
       "3903     Tomas     Satoransky\n",
       "3904     Wayne         Selden\n",
       "3905    Pascal         Siakam\n",
       "3906   Diamond          Stone\n",
       "3907       Edy        Tavares\n",
       "3908    Isaiah         Taylor\n",
       "3909      Mike          Tobey\n",
       "3910     Tyler           Ulis\n",
       "3911    Jarrod         Uthoff\n",
       "3912    Denzel      Valentine\n",
       "3913      Fred       VanVleet\n",
       "3914   Taurean  Waller-Prince\n",
       "3915     Okaro          White\n",
       "3916    Isaiah      Whitehead\n",
       "3917      Troy       Williams\n",
       "3918      Kyle        Wiltjer\n",
       "3919   Stephen      Zimmerman\n",
       "3920      Paul         Zipser\n",
       "3921     Ivica          Zubac\n",
       "\n",
       "[3922 rows x 2 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 使用expand方法\n",
    "df['Player'].str.split(\" \",expand = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "** Index with .str **\n",
    "\n",
    "使用[]对字符串的位置进行索引选取"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       Cur\n",
       "1       Cli\n",
       "2       Leo\n",
       "3       Ed \n",
       "4       Ral\n",
       "5       Gen\n",
       "6       Cha\n",
       "7       Nel\n",
       "8       Jak\n",
       "9       Vin\n",
       "10      Don\n",
       "11      Har\n",
       "12      Joe\n",
       "13      Bob\n",
       "14      Car\n",
       "15      Fra\n",
       "16      Pri\n",
       "17      Bob\n",
       "18      Jim\n",
       "19      Wal\n",
       "20      Jac\n",
       "21      Tom\n",
       "22      Bil\n",
       "23      Don\n",
       "24      Bob\n",
       "25      Jak\n",
       "26      Al \n",
       "27      Joh\n",
       "28      Ler\n",
       "29      Bil\n",
       "       ... \n",
       "3892    Chi\n",
       "3893    Geo\n",
       "3894    Gar\n",
       "3895    Mar\n",
       "3896    Jak\n",
       "3897    Ale\n",
       "3898    Tim\n",
       "3899    Cha\n",
       "3900    Mal\n",
       "3901    Dom\n",
       "3902    Dar\n",
       "3903    Tom\n",
       "3904    Way\n",
       "3905    Pas\n",
       "3906    Dia\n",
       "3907    Edy\n",
       "3908    Isa\n",
       "3909    Mik\n",
       "3910    Tyl\n",
       "3911    Jar\n",
       "3912    Den\n",
       "3913    Fre\n",
       "3914    Tau\n",
       "3915    Oka\n",
       "3916    Isa\n",
       "3917    Tro\n",
       "3918    Kyl\n",
       "3919    Ste\n",
       "3920    Pau\n",
       "3921    Ivi\n",
       "Name: Player, Length: 3922, dtype: object"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Player'].str[:3]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Extracting substring"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<div class=\"girk\">\n",
    "**[点击此处查看：str全部的可以用函数](http://pandas.pydata.org/pandas-docs/stable/text.html#method-summary)**</div><i class=\"fa fa-lightbulb-o \"></i>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 索引选取\n",
    "\n",
    "Object selection has had a number of user-requested additions in order to support more explicit location based indexing. Pandas now supports three types of multi-axis indexing.\n",
    "\n",
    "* **.loc**  is primarily label based, but may also be used with a boolean array. .loc will raise KeyError when the items are not found. Allowed inputs are:\n",
    "\n",
    "    * A single label, e.g. 5 or 'a', (note that 5 is interpreted as a label of the index. This use is not an integer position along the index)\n",
    "    \n",
    "    * A list or array of labels ['a', 'b', 'c']\n",
    "\n",
    "    * A slice object with labels 'a':'f' (note that contrary to usual python slices, both the start and the stop are included, when present in the index! - also see Slicing with labels)\n",
    "\n",
    "    * A boolean array\n",
    "\n",
    "    * A callable function with one argument (the calling Series, DataFrame or Panel) and that returns valid output for indexing (one of the above)\n",
    "\n",
    "\n",
    "See more at Selection by Label\n",
    "\n",
    "* **.iloc**   is primarily integer position based (from 0 to length-1 of the axis), but may also be used with a boolean array. .iloc will raise IndexError if a requested indexer is out-of-bounds, except slice indexers which allow out-of-bounds indexing. (this conforms with python/numpy slice semantics). Allowed inputs are:\n",
    "\n",
    "    * An integer e.g. 5\n",
    "\n",
    "    * A list or array of integers [4, 3, 0]\n",
    "\n",
    "    * A slice object with ints 1:7\n",
    "\n",
    "    * A boolean array\n",
    "\n",
    "    * A callable function with one argument (the calling Series, DataFrame or Panel) and that returns valid output for indexing (one of the above)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>height</th>\n",
       "      <th>weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Curly Armstrong</td>\n",
       "      <td>180.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>Indiana University</td>\n",
       "      <td>1918.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cliff Barker</td>\n",
       "      <td>188.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Yorktown</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leo Barnhorst</td>\n",
       "      <td>193.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ed Bartels</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>North Carolina State University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ralph Beard</td>\n",
       "      <td>178.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Hardinsburg</td>\n",
       "      <td>Kentucky</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Player  height  weight                          collage    born  \\\n",
       "0  Curly Armstrong   180.0    77.0               Indiana University  1918.0   \n",
       "1     Cliff Barker   188.0    83.0           University of Kentucky  1921.0   \n",
       "2    Leo Barnhorst   193.0    86.0         University of Notre Dame  1924.0   \n",
       "3       Ed Bartels   196.0    88.0  North Carolina State University  1925.0   \n",
       "4      Ralph Beard   178.0    79.0           University of Kentucky  1927.0   \n",
       "\n",
       "    birth_city birth_state  \n",
       "0          NaN         NaN  \n",
       "1     Yorktown     Indiana  \n",
       "2          NaN         NaN  \n",
       "3          NaN         NaN  \n",
       "4  Hardinsburg    Kentucky  "
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### .loc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>Height</th>\n",
       "      <th>Weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Curly Armstrong</td>\n",
       "      <td>180.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>Indiana University</td>\n",
       "      <td>1918.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cliff Barker</td>\n",
       "      <td>188.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Yorktown</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leo Barnhorst</td>\n",
       "      <td>193.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ed Bartels</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>North Carolina State University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Gene Berce</td>\n",
       "      <td>180.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Marquette University</td>\n",
       "      <td>1926.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Charlie Black</td>\n",
       "      <td>196.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>University of Kansas</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Arco</td>\n",
       "      <td>Idaho</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Nelson Bobb</td>\n",
       "      <td>183.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>Temple University</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Pennsylvania</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Jake Bornheimer</td>\n",
       "      <td>196.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>Muhlenberg College</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>New Brunswick</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Vince Boryla</td>\n",
       "      <td>196.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>University of Denver</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>East Chicago</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Don Boven</td>\n",
       "      <td>193.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Western Michigan University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>Kalamazoo</td>\n",
       "      <td>Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Harry Boykoff</td>\n",
       "      <td>208.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>St. John's University</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Joe Bradley</td>\n",
       "      <td>190.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Oklahoma State University</td>\n",
       "      <td>1928.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Oklahoma</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Bob Brannum</td>\n",
       "      <td>196.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>Michigan State University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Carl Braun</td>\n",
       "      <td>196.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Colgate University</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Frankie Brian</td>\n",
       "      <td>185.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Louisiana State University</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>Zachary</td>\n",
       "      <td>Louisiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Price Brookfield</td>\n",
       "      <td>193.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>West Texas A&amp;M University</td>\n",
       "      <td>1920.0</td>\n",
       "      <td>Floydada</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Bob Brown</td>\n",
       "      <td>193.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Miami University</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>Versailles</td>\n",
       "      <td>Ohio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Jim Browne</td>\n",
       "      <td>208.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1930.0</td>\n",
       "      <td>Midlothian</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Walt Budko</td>\n",
       "      <td>196.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>Columbia University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>Kearney</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Jack Burmaster</td>\n",
       "      <td>190.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>University of Illinois at Urbana-Champaign</td>\n",
       "      <td>1926.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Tommy Byrnes</td>\n",
       "      <td>190.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Seton Hall University</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>Teaneck</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Bill Calhoun</td>\n",
       "      <td>190.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>City College of San Francisco</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Don Carlson</td>\n",
       "      <td>183.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>University of Minnesota</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>Minneapolis</td>\n",
       "      <td>Minnesota</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Bob Carpenter</td>\n",
       "      <td>196.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>East Texas State University</td>\n",
       "      <td>1917.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Jake Carter</td>\n",
       "      <td>193.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>East Texas State University</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Al Cervi*</td>\n",
       "      <td>180.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1917.0</td>\n",
       "      <td>Buffalo</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>John Chaney</td>\n",
       "      <td>190.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>Louisiana State University</td>\n",
       "      <td>1920.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Leroy Chollet</td>\n",
       "      <td>188.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>Canisius College</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Bill Closs</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Rice University</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>Edge</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Paul Cloyd</td>\n",
       "      <td>188.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>University of Wisconsin</td>\n",
       "      <td>1920.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3891</th>\n",
       "      <td>Daniel Ochefu</td>\n",
       "      <td>211.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>Villanova University</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Baltimore</td>\n",
       "      <td>Maryland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3892</th>\n",
       "      <td>Chinanu Onuaku</td>\n",
       "      <td>208.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>University of Louisville</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Baltimore</td>\n",
       "      <td>Maryland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3893</th>\n",
       "      <td>Georgios Papagiannis</td>\n",
       "      <td>216.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Amarousio</td>\n",
       "      <td>Greece</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3894</th>\n",
       "      <td>Gary Payton</td>\n",
       "      <td>193.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Oregon State University</td>\n",
       "      <td>1968.0</td>\n",
       "      <td>Oakland</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3895</th>\n",
       "      <td>Marshall Plumlee</td>\n",
       "      <td>211.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>Duke University</td>\n",
       "      <td>1990.0</td>\n",
       "      <td>Fort Wayne</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3896</th>\n",
       "      <td>Jakob Poeltl</td>\n",
       "      <td>213.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>University of Utah</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>Vienna</td>\n",
       "      <td>Austria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3897</th>\n",
       "      <td>Alex Poythress</td>\n",
       "      <td>201.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Savannah</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3898</th>\n",
       "      <td>Tim Quarterman</td>\n",
       "      <td>198.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Louisiana State University</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Savannah</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3899</th>\n",
       "      <td>Chasson Randle</td>\n",
       "      <td>188.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>Stanford University</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Rock Island</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3900</th>\n",
       "      <td>Malachi Richardson</td>\n",
       "      <td>198.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Syracuse University</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Trenton</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3901</th>\n",
       "      <td>Domantas Sabonis</td>\n",
       "      <td>211.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>Gonzaga University</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Portland</td>\n",
       "      <td>Oregon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3902</th>\n",
       "      <td>Dario Saric</td>\n",
       "      <td>208.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Sibenik</td>\n",
       "      <td>Croatia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3903</th>\n",
       "      <td>Tomas Satoransky</td>\n",
       "      <td>201.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991.0</td>\n",
       "      <td>Prague</td>\n",
       "      <td>Czech Republic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3904</th>\n",
       "      <td>Wayne Selden</td>\n",
       "      <td>196.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>University of Kansas</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Roxbury</td>\n",
       "      <td>Massachusetts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3905</th>\n",
       "      <td>Pascal Siakam</td>\n",
       "      <td>206.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>New Mexico State University</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Douala</td>\n",
       "      <td>Cameroon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3906</th>\n",
       "      <td>Diamond Stone</td>\n",
       "      <td>211.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>University of Maryland</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Milwaukee</td>\n",
       "      <td>Wisconsin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3907</th>\n",
       "      <td>Edy Tavares</td>\n",
       "      <td>211.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3908</th>\n",
       "      <td>Isaiah Taylor</td>\n",
       "      <td>190.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>University of Texas at Austin</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Hayward</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3909</th>\n",
       "      <td>Mike Tobey</td>\n",
       "      <td>213.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>University of Virginia</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Monroe</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3911</th>\n",
       "      <td>Jarrod Uthoff</td>\n",
       "      <td>206.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>University of Iowa</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Cedar Rapids</td>\n",
       "      <td>Iowa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3912</th>\n",
       "      <td>Denzel Valentine</td>\n",
       "      <td>198.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Michigan State University</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Lansing</td>\n",
       "      <td>Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3913</th>\n",
       "      <td>Fred VanVleet</td>\n",
       "      <td>183.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Wichita State University</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Rockford</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3914</th>\n",
       "      <td>Taurean Waller-Prince</td>\n",
       "      <td>183.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3915</th>\n",
       "      <td>Okaro White</td>\n",
       "      <td>203.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Florida State University</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>Clearwater</td>\n",
       "      <td>Florida</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3916</th>\n",
       "      <td>Isaiah Whitehead</td>\n",
       "      <td>193.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Seton Hall University</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3917</th>\n",
       "      <td>Troy Williams</td>\n",
       "      <td>198.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>South Carolina State University</td>\n",
       "      <td>1969.0</td>\n",
       "      <td>Columbia</td>\n",
       "      <td>South Carolina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3918</th>\n",
       "      <td>Kyle Wiltjer</td>\n",
       "      <td>208.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>Gonzaga University</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>Portland</td>\n",
       "      <td>Oregon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3919</th>\n",
       "      <td>Stephen Zimmerman</td>\n",
       "      <td>213.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>University of Nevada, Las Vegas</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Hendersonville</td>\n",
       "      <td>Tennessee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3920</th>\n",
       "      <td>Paul Zipser</td>\n",
       "      <td>203.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Heidelberg</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3921</th>\n",
       "      <td>Ivica Zubac</td>\n",
       "      <td>216.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Mostar</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3869 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Player  Height  Weight  \\\n",
       "0           Curly Armstrong   180.0    77.0   \n",
       "1              Cliff Barker   188.0    83.0   \n",
       "2             Leo Barnhorst   193.0    86.0   \n",
       "3                Ed Bartels   196.0    88.0   \n",
       "5                Gene Berce   180.0    79.0   \n",
       "6             Charlie Black   196.0    90.0   \n",
       "7               Nelson Bobb   183.0    77.0   \n",
       "8           Jake Bornheimer   196.0    90.0   \n",
       "9              Vince Boryla   196.0    95.0   \n",
       "10                Don Boven   193.0    95.0   \n",
       "11            Harry Boykoff   208.0   102.0   \n",
       "12              Joe Bradley   190.0    79.0   \n",
       "13              Bob Brannum   196.0    97.0   \n",
       "14               Carl Braun   196.0    81.0   \n",
       "15            Frankie Brian   185.0    81.0   \n",
       "16         Price Brookfield   193.0    83.0   \n",
       "17                Bob Brown   193.0    92.0   \n",
       "18               Jim Browne   208.0   106.0   \n",
       "19               Walt Budko   196.0    99.0   \n",
       "20           Jack Burmaster   190.0    86.0   \n",
       "21             Tommy Byrnes   190.0    79.0   \n",
       "22             Bill Calhoun   190.0    81.0   \n",
       "23              Don Carlson   183.0    77.0   \n",
       "24            Bob Carpenter   196.0    90.0   \n",
       "25              Jake Carter   193.0    88.0   \n",
       "26                Al Cervi*   180.0    77.0   \n",
       "27              John Chaney   190.0    83.0   \n",
       "28            Leroy Chollet   188.0    86.0   \n",
       "29               Bill Closs   196.0    88.0   \n",
       "30               Paul Cloyd   188.0    81.0   \n",
       "...                     ...     ...     ...   \n",
       "3891          Daniel Ochefu   211.0   111.0   \n",
       "3892         Chinanu Onuaku   208.0   111.0   \n",
       "3893   Georgios Papagiannis   216.0   108.0   \n",
       "3894            Gary Payton   193.0    81.0   \n",
       "3895       Marshall Plumlee   211.0   111.0   \n",
       "3896           Jakob Poeltl   213.0   112.0   \n",
       "3897         Alex Poythress   201.0   107.0   \n",
       "3898         Tim Quarterman   198.0    88.0   \n",
       "3899         Chasson Randle   188.0    83.0   \n",
       "3900     Malachi Richardson   198.0    92.0   \n",
       "3901       Domantas Sabonis   211.0   108.0   \n",
       "3902            Dario Saric   208.0   101.0   \n",
       "3903       Tomas Satoransky   201.0    95.0   \n",
       "3904           Wayne Selden   196.0   104.0   \n",
       "3905          Pascal Siakam   206.0   104.0   \n",
       "3906          Diamond Stone   211.0   115.0   \n",
       "3907            Edy Tavares   211.0   115.0   \n",
       "3908          Isaiah Taylor   190.0    77.0   \n",
       "3909             Mike Tobey   213.0   117.0   \n",
       "3911          Jarrod Uthoff   206.0   100.0   \n",
       "3912       Denzel Valentine   198.0    96.0   \n",
       "3913          Fred VanVleet   183.0    88.0   \n",
       "3914  Taurean Waller-Prince   183.0    88.0   \n",
       "3915            Okaro White   203.0    92.0   \n",
       "3916       Isaiah Whitehead   193.0    96.0   \n",
       "3917          Troy Williams   198.0    97.0   \n",
       "3918           Kyle Wiltjer   208.0   108.0   \n",
       "3919      Stephen Zimmerman   213.0   108.0   \n",
       "3920            Paul Zipser   203.0    97.0   \n",
       "3921            Ivica Zubac   216.0   120.0   \n",
       "\n",
       "                                         collage    born      birth_city  \\\n",
       "0                             Indiana University  1918.0             NaN   \n",
       "1                         University of Kentucky  1921.0        Yorktown   \n",
       "2                       University of Notre Dame  1924.0             NaN   \n",
       "3                North Carolina State University  1925.0             NaN   \n",
       "5                           Marquette University  1926.0             NaN   \n",
       "6                           University of Kansas  1921.0            Arco   \n",
       "7                              Temple University  1924.0    Philadelphia   \n",
       "8                             Muhlenberg College  1927.0   New Brunswick   \n",
       "9                           University of Denver  1927.0    East Chicago   \n",
       "10                   Western Michigan University  1925.0       Kalamazoo   \n",
       "11                         St. John's University  1922.0        Brooklyn   \n",
       "12                     Oklahoma State University  1928.0      Washington   \n",
       "13                     Michigan State University  1925.0             NaN   \n",
       "14                            Colgate University  1927.0        Brooklyn   \n",
       "15                    Louisiana State University  1923.0         Zachary   \n",
       "16                     West Texas A&M University  1920.0        Floydada   \n",
       "17                              Miami University  1923.0      Versailles   \n",
       "18                                           NaN  1930.0      Midlothian   \n",
       "19                           Columbia University  1925.0         Kearney   \n",
       "20    University of Illinois at Urbana-Champaign  1926.0             NaN   \n",
       "21                         Seton Hall University  1923.0         Teaneck   \n",
       "22                 City College of San Francisco  1927.0   San Francisco   \n",
       "23                       University of Minnesota  1919.0     Minneapolis   \n",
       "24                   East Texas State University  1917.0             NaN   \n",
       "25                   East Texas State University  1924.0             NaN   \n",
       "26                                           NaN  1917.0         Buffalo   \n",
       "27                    Louisiana State University  1920.0             NaN   \n",
       "28                              Canisius College  1925.0     New Orleans   \n",
       "29                               Rice University  1922.0            Edge   \n",
       "30                       University of Wisconsin  1920.0             NaN   \n",
       "...                                          ...     ...             ...   \n",
       "3891                        Villanova University  1993.0       Baltimore   \n",
       "3892                    University of Louisville  1996.0       Baltimore   \n",
       "3893                                         NaN  1997.0       Amarousio   \n",
       "3894                     Oregon State University  1968.0         Oakland   \n",
       "3895                             Duke University  1990.0      Fort Wayne   \n",
       "3896                          University of Utah  1995.0          Vienna   \n",
       "3897                      University of Kentucky  1993.0        Savannah   \n",
       "3898                  Louisiana State University  1994.0        Savannah   \n",
       "3899                         Stanford University  1993.0     Rock Island   \n",
       "3900                         Syracuse University  1996.0         Trenton   \n",
       "3901                          Gonzaga University  1996.0        Portland   \n",
       "3902                                         NaN  1994.0         Sibenik   \n",
       "3903                                         NaN  1991.0          Prague   \n",
       "3904                        University of Kansas  1994.0         Roxbury   \n",
       "3905                 New Mexico State University  1994.0          Douala   \n",
       "3906                      University of Maryland  1997.0       Milwaukee   \n",
       "3907                                         NaN  1997.0             NaN   \n",
       "3908               University of Texas at Austin  1994.0         Hayward   \n",
       "3909                      University of Virginia  1994.0          Monroe   \n",
       "3911                          University of Iowa  1993.0    Cedar Rapids   \n",
       "3912                   Michigan State University  1993.0         Lansing   \n",
       "3913                    Wichita State University  1994.0        Rockford   \n",
       "3914                                         NaN  1994.0             NaN   \n",
       "3915                    Florida State University  1992.0      Clearwater   \n",
       "3916                       Seton Hall University  1995.0        Brooklyn   \n",
       "3917             South Carolina State University  1969.0        Columbia   \n",
       "3918                          Gonzaga University  1992.0        Portland   \n",
       "3919             University of Nevada, Las Vegas  1996.0  Hendersonville   \n",
       "3920                                         NaN  1994.0      Heidelberg   \n",
       "3921                                         NaN  1997.0          Mostar   \n",
       "\n",
       "                 birth_state  \n",
       "0                        NaN  \n",
       "1                    Indiana  \n",
       "2                        NaN  \n",
       "3                        NaN  \n",
       "5                        NaN  \n",
       "6                      Idaho  \n",
       "7               Pennsylvania  \n",
       "8                 New Jersey  \n",
       "9                    Indiana  \n",
       "10                  Michigan  \n",
       "11                  New York  \n",
       "12                  Oklahoma  \n",
       "13                       NaN  \n",
       "14                  New York  \n",
       "15                 Louisiana  \n",
       "16                     Texas  \n",
       "17                      Ohio  \n",
       "18                  Illinois  \n",
       "19                New Jersey  \n",
       "20                       NaN  \n",
       "21                New Jersey  \n",
       "22                California  \n",
       "23                 Minnesota  \n",
       "24                       NaN  \n",
       "25                       NaN  \n",
       "26                  New York  \n",
       "27                       NaN  \n",
       "28                 Louisiana  \n",
       "29                     Texas  \n",
       "30                       NaN  \n",
       "...                      ...  \n",
       "3891                Maryland  \n",
       "3892                Maryland  \n",
       "3893                  Greece  \n",
       "3894              California  \n",
       "3895                 Indiana  \n",
       "3896                 Austria  \n",
       "3897                 Georgia  \n",
       "3898                 Georgia  \n",
       "3899                Illinois  \n",
       "3900              New Jersey  \n",
       "3901                  Oregon  \n",
       "3902                 Croatia  \n",
       "3903          Czech Republic  \n",
       "3904           Massachusetts  \n",
       "3905                Cameroon  \n",
       "3906               Wisconsin  \n",
       "3907                     NaN  \n",
       "3908              California  \n",
       "3909                New York  \n",
       "3911                    Iowa  \n",
       "3912                Michigan  \n",
       "3913                Illinois  \n",
       "3914                     NaN  \n",
       "3915                 Florida  \n",
       "3916                New York  \n",
       "3917          South Carolina  \n",
       "3918                  Oregon  \n",
       "3919               Tennessee  \n",
       "3920                 Germany  \n",
       "3921  Bosnia and Herzegovina  \n",
       "\n",
       "[3869 rows x 7 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#df.loc[df['height']>=180]\n",
    "df.loc[df['Height']>=180]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### .iloc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>height</th>\n",
       "      <th>weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leo Barnhorst</td>\n",
       "      <td>193.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ed Bartels</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>North Carolina State University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ralph Beard</td>\n",
       "      <td>178.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Hardinsburg</td>\n",
       "      <td>Kentucky</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Player  height  weight                          collage    born  \\\n",
       "2  Leo Barnhorst   193.0    86.0         University of Notre Dame  1924.0   \n",
       "3     Ed Bartels   196.0    88.0  North Carolina State University  1925.0   \n",
       "4    Ralph Beard   178.0    79.0           University of Kentucky  1927.0   \n",
       "\n",
       "    birth_city birth_state  \n",
       "2          NaN         NaN  \n",
       "3          NaN         NaN  \n",
       "4  Hardinsburg    Kentucky  "
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[[2,3,4]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>height</th>\n",
       "      <th>weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leo Barnhorst</td>\n",
       "      <td>193.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ed Bartels</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>North Carolina State University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ralph Beard</td>\n",
       "      <td>178.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Hardinsburg</td>\n",
       "      <td>Kentucky</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          Player  height  weight                          collage    born  \\\n",
       "2  Leo Barnhorst   193.0    86.0         University of Notre Dame  1924.0   \n",
       "3     Ed Bartels   196.0    88.0  North Carolina State University  1925.0   \n",
       "4    Ralph Beard   178.0    79.0           University of Kentucky  1927.0   \n",
       "\n",
       "    birth_city birth_state  \n",
       "2          NaN         NaN  \n",
       "3          NaN         NaN  \n",
       "4  Hardinsburg    Kentucky  "
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[[2,3,4]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df1 = df.set_index(\"Player\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>height</th>\n",
       "      <th>weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Player</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Leo Barnhorst</th>\n",
       "      <td>193.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ralph Beard</th>\n",
       "      <td>178.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Hardinsburg</td>\n",
       "      <td>Kentucky</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               height  weight                   collage    born   birth_city  \\\n",
       "Player                                                                         \n",
       "Leo Barnhorst   193.0    86.0  University of Notre Dame  1924.0          NaN   \n",
       "Ralph Beard     178.0    79.0    University of Kentucky  1927.0  Hardinsburg   \n",
       "\n",
       "              birth_state  \n",
       "Player                     \n",
       "Leo Barnhorst         NaN  \n",
       "Ralph Beard      Kentucky  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.loc[[\"Leo Barnhorst\",\"Ralph Beard\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>height</th>\n",
       "      <th>weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Player</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Curly Armstrong</th>\n",
       "      <td>180.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>Indiana University</td>\n",
       "      <td>1918.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Cliff Barker</th>\n",
       "      <td>188.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Yorktown</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Leo Barnhorst</th>\n",
       "      <td>193.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 height  weight                   collage    born birth_city  \\\n",
       "Player                                                                         \n",
       "Curly Armstrong   180.0    77.0        Indiana University  1918.0        NaN   \n",
       "Cliff Barker      188.0    83.0    University of Kentucky  1921.0   Yorktown   \n",
       "Leo Barnhorst     193.0    86.0  University of Notre Dame  1924.0        NaN   \n",
       "\n",
       "                birth_state  \n",
       "Player                       \n",
       "Curly Armstrong         NaN  \n",
       "Cliff Barker        Indiana  \n",
       "Leo Barnhorst           NaN  "
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.iloc[[0,1,2]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>height</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Curly Armstrong</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cliff Barker</td>\n",
       "      <td>188.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leo Barnhorst</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ed Bartels</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ralph Beard</td>\n",
       "      <td>178.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Gene Berce</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Charlie Black</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Nelson Bobb</td>\n",
       "      <td>183.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Jake Bornheimer</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Vince Boryla</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Player  height\n",
       "0  Curly Armstrong   180.0\n",
       "1     Cliff Barker   188.0\n",
       "2    Leo Barnhorst   193.0\n",
       "3       Ed Bartels   196.0\n",
       "4      Ralph Beard   178.0\n",
       "5       Gene Berce   180.0\n",
       "6    Charlie Black   196.0\n",
       "7      Nelson Bobb   183.0\n",
       "8  Jake Bornheimer   196.0\n",
       "9     Vince Boryla   196.0"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.iloc[:10,[0,1]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>height</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Curly Armstrong</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cliff Barker</td>\n",
       "      <td>188.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leo Barnhorst</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ed Bartels</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ralph Beard</td>\n",
       "      <td>178.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Gene Berce</td>\n",
       "      <td>180.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Charlie Black</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Nelson Bobb</td>\n",
       "      <td>183.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Jake Bornheimer</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Vince Boryla</td>\n",
       "      <td>196.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Don Boven</td>\n",
       "      <td>193.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Player  height\n",
       "0   Curly Armstrong   180.0\n",
       "1      Cliff Barker   188.0\n",
       "2     Leo Barnhorst   193.0\n",
       "3        Ed Bartels   196.0\n",
       "4       Ralph Beard   178.0\n",
       "5        Gene Berce   180.0\n",
       "6     Charlie Black   196.0\n",
       "7       Nelson Bobb   183.0\n",
       "8   Jake Bornheimer   196.0\n",
       "9      Vince Boryla   196.0\n",
       "10        Don Boven   193.0"
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[:10,['Player','height']]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 数据过滤\n",
    "\n",
    "基于loc的强大功能，我们可以对数据做很多复杂的操作。第一个就是实现数据的过滤，类似于SQL里面的where功能\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "选取出height >= 180 ,weight >= 80的运动员数据。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>height</th>\n",
       "      <th>weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cliff Barker</td>\n",
       "      <td>188.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Yorktown</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leo Barnhorst</td>\n",
       "      <td>193.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ed Bartels</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>North Carolina State University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Charlie Black</td>\n",
       "      <td>196.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>University of Kansas</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Arco</td>\n",
       "      <td>Idaho</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Jake Bornheimer</td>\n",
       "      <td>196.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>Muhlenberg College</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>New Brunswick</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Vince Boryla</td>\n",
       "      <td>196.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>University of Denver</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>East Chicago</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Don Boven</td>\n",
       "      <td>193.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Western Michigan University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>Kalamazoo</td>\n",
       "      <td>Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Harry Boykoff</td>\n",
       "      <td>208.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>St. John's University</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Bob Brannum</td>\n",
       "      <td>196.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>Michigan State University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Carl Braun</td>\n",
       "      <td>196.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Colgate University</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Frankie Brian</td>\n",
       "      <td>185.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Louisiana State University</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>Zachary</td>\n",
       "      <td>Louisiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Price Brookfield</td>\n",
       "      <td>193.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>West Texas A&amp;M University</td>\n",
       "      <td>1920.0</td>\n",
       "      <td>Floydada</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Bob Brown</td>\n",
       "      <td>193.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Miami University</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>Versailles</td>\n",
       "      <td>Ohio</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Jim Browne</td>\n",
       "      <td>208.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1930.0</td>\n",
       "      <td>Midlothian</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Walt Budko</td>\n",
       "      <td>196.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>Columbia University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>Kearney</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Jack Burmaster</td>\n",
       "      <td>190.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>University of Illinois at Urbana-Champaign</td>\n",
       "      <td>1926.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Bill Calhoun</td>\n",
       "      <td>190.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>City College of San Francisco</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>San Francisco</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Bob Carpenter</td>\n",
       "      <td>196.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>East Texas State University</td>\n",
       "      <td>1917.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Jake Carter</td>\n",
       "      <td>193.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>East Texas State University</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>John Chaney</td>\n",
       "      <td>190.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>Louisiana State University</td>\n",
       "      <td>1920.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Leroy Chollet</td>\n",
       "      <td>188.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>Canisius College</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>New Orleans</td>\n",
       "      <td>Louisiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Bill Closs</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Rice University</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>Edge</td>\n",
       "      <td>Texas</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Paul Cloyd</td>\n",
       "      <td>188.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>University of Wisconsin</td>\n",
       "      <td>1920.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Jack Coleman</td>\n",
       "      <td>201.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>University of Louisville</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>Burgin</td>\n",
       "      <td>Kentucky</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Ray Corley</td>\n",
       "      <td>183.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Georgetown University</td>\n",
       "      <td>1928.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Jack Cotton</td>\n",
       "      <td>201.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>University of Wyoming</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>Miles City</td>\n",
       "      <td>Montana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Dillard Crocker</td>\n",
       "      <td>193.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Western Michigan University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>Coffee County</td>\n",
       "      <td>Tennessee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Hook Dillon</td>\n",
       "      <td>190.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>University of North Carolina</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>Savannah</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Bob Doll</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>University of Colorado</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>Steamboat Springs</td>\n",
       "      <td>Colorado</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Harry Donovan</td>\n",
       "      <td>188.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Muhlenberg College</td>\n",
       "      <td>1926.0</td>\n",
       "      <td>Union City</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3890</th>\n",
       "      <td>David Nwaba</td>\n",
       "      <td>193.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>California Polytechnic State University, San L...</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Los Angeles</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3891</th>\n",
       "      <td>Daniel Ochefu</td>\n",
       "      <td>211.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>Villanova University</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Baltimore</td>\n",
       "      <td>Maryland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3892</th>\n",
       "      <td>Chinanu Onuaku</td>\n",
       "      <td>208.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>University of Louisville</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Baltimore</td>\n",
       "      <td>Maryland</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3893</th>\n",
       "      <td>Georgios Papagiannis</td>\n",
       "      <td>216.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Amarousio</td>\n",
       "      <td>Greece</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3894</th>\n",
       "      <td>Gary Payton</td>\n",
       "      <td>193.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Oregon State University</td>\n",
       "      <td>1968.0</td>\n",
       "      <td>Oakland</td>\n",
       "      <td>California</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3895</th>\n",
       "      <td>Marshall Plumlee</td>\n",
       "      <td>211.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>Duke University</td>\n",
       "      <td>1990.0</td>\n",
       "      <td>Fort Wayne</td>\n",
       "      <td>Indiana</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3896</th>\n",
       "      <td>Jakob Poeltl</td>\n",
       "      <td>213.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>University of Utah</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>Vienna</td>\n",
       "      <td>Austria</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3897</th>\n",
       "      <td>Alex Poythress</td>\n",
       "      <td>201.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Savannah</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3898</th>\n",
       "      <td>Tim Quarterman</td>\n",
       "      <td>198.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Louisiana State University</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Savannah</td>\n",
       "      <td>Georgia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3899</th>\n",
       "      <td>Chasson Randle</td>\n",
       "      <td>188.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>Stanford University</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Rock Island</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3900</th>\n",
       "      <td>Malachi Richardson</td>\n",
       "      <td>198.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Syracuse University</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Trenton</td>\n",
       "      <td>New Jersey</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3901</th>\n",
       "      <td>Domantas Sabonis</td>\n",
       "      <td>211.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>Gonzaga University</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Portland</td>\n",
       "      <td>Oregon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3902</th>\n",
       "      <td>Dario Saric</td>\n",
       "      <td>208.0</td>\n",
       "      <td>101.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Sibenik</td>\n",
       "      <td>Croatia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3903</th>\n",
       "      <td>Tomas Satoransky</td>\n",
       "      <td>201.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1991.0</td>\n",
       "      <td>Prague</td>\n",
       "      <td>Czech Republic</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3904</th>\n",
       "      <td>Wayne Selden</td>\n",
       "      <td>196.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>University of Kansas</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Roxbury</td>\n",
       "      <td>Massachusetts</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3905</th>\n",
       "      <td>Pascal Siakam</td>\n",
       "      <td>206.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>New Mexico State University</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Douala</td>\n",
       "      <td>Cameroon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3906</th>\n",
       "      <td>Diamond Stone</td>\n",
       "      <td>211.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>University of Maryland</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Milwaukee</td>\n",
       "      <td>Wisconsin</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3907</th>\n",
       "      <td>Edy Tavares</td>\n",
       "      <td>211.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3909</th>\n",
       "      <td>Mike Tobey</td>\n",
       "      <td>213.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>University of Virginia</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Monroe</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3911</th>\n",
       "      <td>Jarrod Uthoff</td>\n",
       "      <td>206.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>University of Iowa</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Cedar Rapids</td>\n",
       "      <td>Iowa</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3912</th>\n",
       "      <td>Denzel Valentine</td>\n",
       "      <td>198.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Michigan State University</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>Lansing</td>\n",
       "      <td>Michigan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3913</th>\n",
       "      <td>Fred VanVleet</td>\n",
       "      <td>183.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Wichita State University</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Rockford</td>\n",
       "      <td>Illinois</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3914</th>\n",
       "      <td>Taurean Waller-Prince</td>\n",
       "      <td>183.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3915</th>\n",
       "      <td>Okaro White</td>\n",
       "      <td>203.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Florida State University</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>Clearwater</td>\n",
       "      <td>Florida</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3916</th>\n",
       "      <td>Isaiah Whitehead</td>\n",
       "      <td>193.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>Seton Hall University</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3917</th>\n",
       "      <td>Troy Williams</td>\n",
       "      <td>198.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>South Carolina State University</td>\n",
       "      <td>1969.0</td>\n",
       "      <td>Columbia</td>\n",
       "      <td>South Carolina</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3918</th>\n",
       "      <td>Kyle Wiltjer</td>\n",
       "      <td>208.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>Gonzaga University</td>\n",
       "      <td>1992.0</td>\n",
       "      <td>Portland</td>\n",
       "      <td>Oregon</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3919</th>\n",
       "      <td>Stephen Zimmerman</td>\n",
       "      <td>213.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>University of Nevada, Las Vegas</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>Hendersonville</td>\n",
       "      <td>Tennessee</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3920</th>\n",
       "      <td>Paul Zipser</td>\n",
       "      <td>203.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>Heidelberg</td>\n",
       "      <td>Germany</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3921</th>\n",
       "      <td>Ivica Zubac</td>\n",
       "      <td>216.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>Mostar</td>\n",
       "      <td>Bosnia and Herzegovina</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>3543 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Player  height  weight  \\\n",
       "1              Cliff Barker   188.0    83.0   \n",
       "2             Leo Barnhorst   193.0    86.0   \n",
       "3                Ed Bartels   196.0    88.0   \n",
       "6             Charlie Black   196.0    90.0   \n",
       "8           Jake Bornheimer   196.0    90.0   \n",
       "9              Vince Boryla   196.0    95.0   \n",
       "10                Don Boven   193.0    95.0   \n",
       "11            Harry Boykoff   208.0   102.0   \n",
       "13              Bob Brannum   196.0    97.0   \n",
       "14               Carl Braun   196.0    81.0   \n",
       "15            Frankie Brian   185.0    81.0   \n",
       "16         Price Brookfield   193.0    83.0   \n",
       "17                Bob Brown   193.0    92.0   \n",
       "18               Jim Browne   208.0   106.0   \n",
       "19               Walt Budko   196.0    99.0   \n",
       "20           Jack Burmaster   190.0    86.0   \n",
       "22             Bill Calhoun   190.0    81.0   \n",
       "24            Bob Carpenter   196.0    90.0   \n",
       "25              Jake Carter   193.0    88.0   \n",
       "27              John Chaney   190.0    83.0   \n",
       "28            Leroy Chollet   188.0    86.0   \n",
       "29               Bill Closs   196.0    88.0   \n",
       "30               Paul Cloyd   188.0    81.0   \n",
       "31             Jack Coleman   201.0    88.0   \n",
       "33               Ray Corley   183.0    81.0   \n",
       "34              Jack Cotton   201.0    90.0   \n",
       "35          Dillard Crocker   193.0    92.0   \n",
       "40              Hook Dillon   190.0    81.0   \n",
       "43                 Bob Doll   196.0    88.0   \n",
       "44            Harry Donovan   188.0    81.0   \n",
       "...                     ...     ...     ...   \n",
       "3890            David Nwaba   193.0    94.0   \n",
       "3891          Daniel Ochefu   211.0   111.0   \n",
       "3892         Chinanu Onuaku   208.0   111.0   \n",
       "3893   Georgios Papagiannis   216.0   108.0   \n",
       "3894            Gary Payton   193.0    81.0   \n",
       "3895       Marshall Plumlee   211.0   111.0   \n",
       "3896           Jakob Poeltl   213.0   112.0   \n",
       "3897         Alex Poythress   201.0   107.0   \n",
       "3898         Tim Quarterman   198.0    88.0   \n",
       "3899         Chasson Randle   188.0    83.0   \n",
       "3900     Malachi Richardson   198.0    92.0   \n",
       "3901       Domantas Sabonis   211.0   108.0   \n",
       "3902            Dario Saric   208.0   101.0   \n",
       "3903       Tomas Satoransky   201.0    95.0   \n",
       "3904           Wayne Selden   196.0   104.0   \n",
       "3905          Pascal Siakam   206.0   104.0   \n",
       "3906          Diamond Stone   211.0   115.0   \n",
       "3907            Edy Tavares   211.0   115.0   \n",
       "3909             Mike Tobey   213.0   117.0   \n",
       "3911          Jarrod Uthoff   206.0   100.0   \n",
       "3912       Denzel Valentine   198.0    96.0   \n",
       "3913          Fred VanVleet   183.0    88.0   \n",
       "3914  Taurean Waller-Prince   183.0    88.0   \n",
       "3915            Okaro White   203.0    92.0   \n",
       "3916       Isaiah Whitehead   193.0    96.0   \n",
       "3917          Troy Williams   198.0    97.0   \n",
       "3918           Kyle Wiltjer   208.0   108.0   \n",
       "3919      Stephen Zimmerman   213.0   108.0   \n",
       "3920            Paul Zipser   203.0    97.0   \n",
       "3921            Ivica Zubac   216.0   120.0   \n",
       "\n",
       "                                                collage    born  \\\n",
       "1                                University of Kentucky  1921.0   \n",
       "2                              University of Notre Dame  1924.0   \n",
       "3                       North Carolina State University  1925.0   \n",
       "6                                  University of Kansas  1921.0   \n",
       "8                                    Muhlenberg College  1927.0   \n",
       "9                                  University of Denver  1927.0   \n",
       "10                          Western Michigan University  1925.0   \n",
       "11                                St. John's University  1922.0   \n",
       "13                            Michigan State University  1925.0   \n",
       "14                                   Colgate University  1927.0   \n",
       "15                           Louisiana State University  1923.0   \n",
       "16                            West Texas A&M University  1920.0   \n",
       "17                                     Miami University  1923.0   \n",
       "18                                                  NaN  1930.0   \n",
       "19                                  Columbia University  1925.0   \n",
       "20           University of Illinois at Urbana-Champaign  1926.0   \n",
       "22                        City College of San Francisco  1927.0   \n",
       "24                          East Texas State University  1917.0   \n",
       "25                          East Texas State University  1924.0   \n",
       "27                           Louisiana State University  1920.0   \n",
       "28                                     Canisius College  1925.0   \n",
       "29                                      Rice University  1922.0   \n",
       "30                              University of Wisconsin  1920.0   \n",
       "31                             University of Louisville  1924.0   \n",
       "33                                Georgetown University  1928.0   \n",
       "34                                University of Wyoming  1924.0   \n",
       "35                          Western Michigan University  1925.0   \n",
       "40                         University of North Carolina  1924.0   \n",
       "43                               University of Colorado  1919.0   \n",
       "44                                   Muhlenberg College  1926.0   \n",
       "...                                                 ...     ...   \n",
       "3890  California Polytechnic State University, San L...  1993.0   \n",
       "3891                               Villanova University  1993.0   \n",
       "3892                           University of Louisville  1996.0   \n",
       "3893                                                NaN  1997.0   \n",
       "3894                            Oregon State University  1968.0   \n",
       "3895                                    Duke University  1990.0   \n",
       "3896                                 University of Utah  1995.0   \n",
       "3897                             University of Kentucky  1993.0   \n",
       "3898                         Louisiana State University  1994.0   \n",
       "3899                                Stanford University  1993.0   \n",
       "3900                                Syracuse University  1996.0   \n",
       "3901                                 Gonzaga University  1996.0   \n",
       "3902                                                NaN  1994.0   \n",
       "3903                                                NaN  1991.0   \n",
       "3904                               University of Kansas  1994.0   \n",
       "3905                        New Mexico State University  1994.0   \n",
       "3906                             University of Maryland  1997.0   \n",
       "3907                                                NaN  1997.0   \n",
       "3909                             University of Virginia  1994.0   \n",
       "3911                                 University of Iowa  1993.0   \n",
       "3912                          Michigan State University  1993.0   \n",
       "3913                           Wichita State University  1994.0   \n",
       "3914                                                NaN  1994.0   \n",
       "3915                           Florida State University  1992.0   \n",
       "3916                              Seton Hall University  1995.0   \n",
       "3917                    South Carolina State University  1969.0   \n",
       "3918                                 Gonzaga University  1992.0   \n",
       "3919                    University of Nevada, Las Vegas  1996.0   \n",
       "3920                                                NaN  1994.0   \n",
       "3921                                                NaN  1997.0   \n",
       "\n",
       "             birth_city             birth_state  \n",
       "1              Yorktown                 Indiana  \n",
       "2                   NaN                     NaN  \n",
       "3                   NaN                     NaN  \n",
       "6                  Arco                   Idaho  \n",
       "8         New Brunswick              New Jersey  \n",
       "9          East Chicago                 Indiana  \n",
       "10            Kalamazoo                Michigan  \n",
       "11             Brooklyn                New York  \n",
       "13                  NaN                     NaN  \n",
       "14             Brooklyn                New York  \n",
       "15              Zachary               Louisiana  \n",
       "16             Floydada                   Texas  \n",
       "17           Versailles                    Ohio  \n",
       "18           Midlothian                Illinois  \n",
       "19              Kearney              New Jersey  \n",
       "20                  NaN                     NaN  \n",
       "22        San Francisco              California  \n",
       "24                  NaN                     NaN  \n",
       "25                  NaN                     NaN  \n",
       "27                  NaN                     NaN  \n",
       "28          New Orleans               Louisiana  \n",
       "29                 Edge                   Texas  \n",
       "30                  NaN                     NaN  \n",
       "31               Burgin                Kentucky  \n",
       "33                  NaN                     NaN  \n",
       "34           Miles City                 Montana  \n",
       "35        Coffee County               Tennessee  \n",
       "40             Savannah                 Georgia  \n",
       "43    Steamboat Springs                Colorado  \n",
       "44           Union City              New Jersey  \n",
       "...                 ...                     ...  \n",
       "3890        Los Angeles              California  \n",
       "3891          Baltimore                Maryland  \n",
       "3892          Baltimore                Maryland  \n",
       "3893          Amarousio                  Greece  \n",
       "3894            Oakland              California  \n",
       "3895         Fort Wayne                 Indiana  \n",
       "3896             Vienna                 Austria  \n",
       "3897           Savannah                 Georgia  \n",
       "3898           Savannah                 Georgia  \n",
       "3899        Rock Island                Illinois  \n",
       "3900            Trenton              New Jersey  \n",
       "3901           Portland                  Oregon  \n",
       "3902            Sibenik                 Croatia  \n",
       "3903             Prague          Czech Republic  \n",
       "3904            Roxbury           Massachusetts  \n",
       "3905             Douala                Cameroon  \n",
       "3906          Milwaukee               Wisconsin  \n",
       "3907                NaN                     NaN  \n",
       "3909             Monroe                New York  \n",
       "3911       Cedar Rapids                    Iowa  \n",
       "3912            Lansing                Michigan  \n",
       "3913           Rockford                Illinois  \n",
       "3914                NaN                     NaN  \n",
       "3915         Clearwater                 Florida  \n",
       "3916           Brooklyn                New York  \n",
       "3917           Columbia          South Carolina  \n",
       "3918           Portland                  Oregon  \n",
       "3919     Hendersonville               Tennessee  \n",
       "3920         Heidelberg                 Germany  \n",
       "3921             Mostar  Bosnia and Herzegovina  \n",
       "\n",
       "[3543 rows x 7 columns]"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[(df['height']>=180) & (df['weight']>=80)]\n",
    "\n",
    "df[(df['height']>=180) & (df['weight']>=80)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "solution2": "shown",
    "solution2_first": true
   },
   "source": [
    "上面两种方法都可以，似乎没体现出.loc有什么优势。那么我们换个提问：\n",
    "\n",
    "创建一个新列，\n",
    "* 如果height >= 180, weight >=80, 值为 “high\"\n",
    "* 如果height<= 180 并且 height >=170, weight<= 80 并且 weight >=70 值为 ”msize\"\n",
    "* 其余的值为 \"small\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {
    "solution2": "shown"
   },
   "outputs": [],
   "source": [
    "df.loc[(df['height'] >=180) & (df['weight'] >=80),\"flag\"] = \"high\"\n",
    "df.loc[((df['height'] <=180) & (df['height']>=170)) &  ((df['weight'] <=80) & (df['weight'] >=70)),\"flag\"] = \"msize\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>height</th>\n",
       "      <th>weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "      <th>flag</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Curly Armstrong</td>\n",
       "      <td>180.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>Indiana University</td>\n",
       "      <td>1918.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>msize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Cliff Barker</td>\n",
       "      <td>188.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Yorktown</td>\n",
       "      <td>Indiana</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Leo Barnhorst</td>\n",
       "      <td>193.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Ed Bartels</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>North Carolina State University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Ralph Beard</td>\n",
       "      <td>178.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Hardinsburg</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>msize</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            Player  height  weight                          collage    born  \\\n",
       "0  Curly Armstrong   180.0    77.0               Indiana University  1918.0   \n",
       "1     Cliff Barker   188.0    83.0           University of Kentucky  1921.0   \n",
       "2    Leo Barnhorst   193.0    86.0         University of Notre Dame  1924.0   \n",
       "3       Ed Bartels   196.0    88.0  North Carolina State University  1925.0   \n",
       "4      Ralph Beard   178.0    79.0           University of Kentucky  1927.0   \n",
       "\n",
       "    birth_city birth_state   flag  \n",
       "0          NaN         NaN  msize  \n",
       "1     Yorktown     Indiana   high  \n",
       "2          NaN         NaN   high  \n",
       "3          NaN         NaN   high  \n",
       "4  Hardinsburg    Kentucky  msize  "
      ]
     },
     "execution_count": 92,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 93,
   "metadata": {
    "collapsed": true,
    "solution2": "shown"
   },
   "outputs": [],
   "source": [
    "df.loc[~(((df['height'] >=180) & (df['weight'] >=80)) |(((df['height'] <=180) & (df['height']>=170))&((df['weight'] <=80) & (df['weight'] >=70)))),\"flag\"] = \"small\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "high     3542\n",
       "small     311\n",
       "msize      69\n",
       "Name: flag, dtype: int64"
      ]
     },
     "execution_count": 94,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['flag'].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### MultiIndex"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Player          object\n",
       "height         float64\n",
       "weight         float64\n",
       "collage         object\n",
       "born           float64\n",
       "birth_city      object\n",
       "birth_state     object\n",
       "dtype: object"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df = df.set_index(keys=['birth_city','birth_state'],append=True,drop = False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 108,
   "metadata": {},
   "outputs": [],
   "source": [
    "new_df.sort_index(na_position=\"last\",inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>height</th>\n",
       "      <th>weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "      <th>flag</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <td>Curly Armstrong</td>\n",
       "      <td>180.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>Indiana University</td>\n",
       "      <td>1918.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>msize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <th>Yorktown</th>\n",
       "      <th>Indiana</th>\n",
       "      <td>Cliff Barker</td>\n",
       "      <td>188.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Yorktown</td>\n",
       "      <td>Indiana</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <td>Leo Barnhorst</td>\n",
       "      <td>193.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>University of Notre Dame</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <td>Ed Bartels</td>\n",
       "      <td>196.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>North Carolina State University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <th>Hardinsburg</th>\n",
       "      <th>Kentucky</th>\n",
       "      <td>Ralph Beard</td>\n",
       "      <td>178.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>University of Kentucky</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Hardinsburg</td>\n",
       "      <td>Kentucky</td>\n",
       "      <td>msize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <td>Gene Berce</td>\n",
       "      <td>180.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Marquette University</td>\n",
       "      <td>1926.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>msize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <th>Arco</th>\n",
       "      <th>Idaho</th>\n",
       "      <td>Charlie Black</td>\n",
       "      <td>196.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>University of Kansas</td>\n",
       "      <td>1921.0</td>\n",
       "      <td>Arco</td>\n",
       "      <td>Idaho</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <th>Philadelphia</th>\n",
       "      <th>Pennsylvania</th>\n",
       "      <td>Nelson Bobb</td>\n",
       "      <td>183.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>Temple University</td>\n",
       "      <td>1924.0</td>\n",
       "      <td>Philadelphia</td>\n",
       "      <td>Pennsylvania</td>\n",
       "      <td>small</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <th>New Brunswick</th>\n",
       "      <th>New Jersey</th>\n",
       "      <td>Jake Bornheimer</td>\n",
       "      <td>196.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>Muhlenberg College</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>New Brunswick</td>\n",
       "      <td>New Jersey</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <th>East Chicago</th>\n",
       "      <th>Indiana</th>\n",
       "      <td>Vince Boryla</td>\n",
       "      <td>196.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>University of Denver</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>East Chicago</td>\n",
       "      <td>Indiana</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <th>Kalamazoo</th>\n",
       "      <th>Michigan</th>\n",
       "      <td>Don Boven</td>\n",
       "      <td>193.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>Western Michigan University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>Kalamazoo</td>\n",
       "      <td>Michigan</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <th>Brooklyn</th>\n",
       "      <th>New York</th>\n",
       "      <td>Harry Boykoff</td>\n",
       "      <td>208.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>St. John's University</td>\n",
       "      <td>1922.0</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <th>Washington</th>\n",
       "      <th>Oklahoma</th>\n",
       "      <td>Joe Bradley</td>\n",
       "      <td>190.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>Oklahoma State University</td>\n",
       "      <td>1928.0</td>\n",
       "      <td>Washington</td>\n",
       "      <td>Oklahoma</td>\n",
       "      <td>small</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <th>NaN</th>\n",
       "      <th>NaN</th>\n",
       "      <td>Bob Brannum</td>\n",
       "      <td>196.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>Michigan State University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <th>Brooklyn</th>\n",
       "      <th>New York</th>\n",
       "      <td>Carl Braun</td>\n",
       "      <td>196.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Colgate University</td>\n",
       "      <td>1927.0</td>\n",
       "      <td>Brooklyn</td>\n",
       "      <td>New York</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <th>Zachary</th>\n",
       "      <th>Louisiana</th>\n",
       "      <td>Frankie Brian</td>\n",
       "      <td>185.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Louisiana State University</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>Zachary</td>\n",
       "      <td>Louisiana</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <th>Floydada</th>\n",
       "      <th>Texas</th>\n",
       "      <td>Price Brookfield</td>\n",
       "      <td>193.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>West Texas A&amp;M University</td>\n",
       "      <td>1920.0</td>\n",
       "      <td>Floydada</td>\n",
       "      <td>Texas</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <th>Versailles</th>\n",
       "      <th>Ohio</th>\n",
       "      <td>Bob Brown</td>\n",
       "      <td>193.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>Miami University</td>\n",
       "      <td>1923.0</td>\n",
       "      <td>Versailles</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <th>Midlothian</th>\n",
       "      <th>Illinois</th>\n",
       "      <td>Jim Browne</td>\n",
       "      <td>208.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1930.0</td>\n",
       "      <td>Midlothian</td>\n",
       "      <td>Illinois</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <th>Kearney</th>\n",
       "      <th>New Jersey</th>\n",
       "      <td>Walt Budko</td>\n",
       "      <td>196.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>Columbia University</td>\n",
       "      <td>1925.0</td>\n",
       "      <td>Kearney</td>\n",
       "      <td>New Jersey</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         Player  height  weight  \\\n",
       "   birth_city    birth_state                                      \n",
       "0  NaN           NaN            Curly Armstrong   180.0    77.0   \n",
       "1  Yorktown      Indiana           Cliff Barker   188.0    83.0   \n",
       "2  NaN           NaN              Leo Barnhorst   193.0    86.0   \n",
       "3  NaN           NaN                 Ed Bartels   196.0    88.0   \n",
       "4  Hardinsburg   Kentucky           Ralph Beard   178.0    79.0   \n",
       "5  NaN           NaN                 Gene Berce   180.0    79.0   \n",
       "6  Arco          Idaho            Charlie Black   196.0    90.0   \n",
       "7  Philadelphia  Pennsylvania       Nelson Bobb   183.0    77.0   \n",
       "8  New Brunswick New Jersey     Jake Bornheimer   196.0    90.0   \n",
       "9  East Chicago  Indiana           Vince Boryla   196.0    95.0   \n",
       "10 Kalamazoo     Michigan             Don Boven   193.0    95.0   \n",
       "11 Brooklyn      New York         Harry Boykoff   208.0   102.0   \n",
       "12 Washington    Oklahoma           Joe Bradley   190.0    79.0   \n",
       "13 NaN           NaN                Bob Brannum   196.0    97.0   \n",
       "14 Brooklyn      New York            Carl Braun   196.0    81.0   \n",
       "15 Zachary       Louisiana        Frankie Brian   185.0    81.0   \n",
       "16 Floydada      Texas         Price Brookfield   193.0    83.0   \n",
       "17 Versailles    Ohio                 Bob Brown   193.0    92.0   \n",
       "18 Midlothian    Illinois            Jim Browne   208.0   106.0   \n",
       "19 Kearney       New Jersey          Walt Budko   196.0    99.0   \n",
       "\n",
       "                                                       collage    born  \\\n",
       "   birth_city    birth_state                                             \n",
       "0  NaN           NaN                        Indiana University  1918.0   \n",
       "1  Yorktown      Indiana                University of Kentucky  1921.0   \n",
       "2  NaN           NaN                  University of Notre Dame  1924.0   \n",
       "3  NaN           NaN           North Carolina State University  1925.0   \n",
       "4  Hardinsburg   Kentucky               University of Kentucky  1927.0   \n",
       "5  NaN           NaN                      Marquette University  1926.0   \n",
       "6  Arco          Idaho                    University of Kansas  1921.0   \n",
       "7  Philadelphia  Pennsylvania                Temple University  1924.0   \n",
       "8  New Brunswick New Jersey                 Muhlenberg College  1927.0   \n",
       "9  East Chicago  Indiana                  University of Denver  1927.0   \n",
       "10 Kalamazoo     Michigan          Western Michigan University  1925.0   \n",
       "11 Brooklyn      New York                St. John's University  1922.0   \n",
       "12 Washington    Oklahoma            Oklahoma State University  1928.0   \n",
       "13 NaN           NaN                 Michigan State University  1925.0   \n",
       "14 Brooklyn      New York                   Colgate University  1927.0   \n",
       "15 Zachary       Louisiana          Louisiana State University  1923.0   \n",
       "16 Floydada      Texas               West Texas A&M University  1920.0   \n",
       "17 Versailles    Ohio                         Miami University  1923.0   \n",
       "18 Midlothian    Illinois                                  NaN  1930.0   \n",
       "19 Kearney       New Jersey                Columbia University  1925.0   \n",
       "\n",
       "                                  birth_city   birth_state   flag  \n",
       "   birth_city    birth_state                                       \n",
       "0  NaN           NaN                     NaN           NaN  msize  \n",
       "1  Yorktown      Indiana            Yorktown       Indiana   high  \n",
       "2  NaN           NaN                     NaN           NaN   high  \n",
       "3  NaN           NaN                     NaN           NaN   high  \n",
       "4  Hardinsburg   Kentucky        Hardinsburg      Kentucky  msize  \n",
       "5  NaN           NaN                     NaN           NaN  msize  \n",
       "6  Arco          Idaho                  Arco         Idaho   high  \n",
       "7  Philadelphia  Pennsylvania   Philadelphia  Pennsylvania  small  \n",
       "8  New Brunswick New Jersey    New Brunswick    New Jersey   high  \n",
       "9  East Chicago  Indiana        East Chicago       Indiana   high  \n",
       "10 Kalamazoo     Michigan          Kalamazoo      Michigan   high  \n",
       "11 Brooklyn      New York           Brooklyn      New York   high  \n",
       "12 Washington    Oklahoma         Washington      Oklahoma  small  \n",
       "13 NaN           NaN                     NaN           NaN   high  \n",
       "14 Brooklyn      New York           Brooklyn      New York   high  \n",
       "15 Zachary       Louisiana           Zachary     Louisiana   high  \n",
       "16 Floydada      Texas              Floydada         Texas   high  \n",
       "17 Versailles    Ohio             Versailles          Ohio   high  \n",
       "18 Midlothian    Illinois         Midlothian      Illinois   high  \n",
       "19 Kearney       New Jersey          Kearney    New Jersey   high  "
      ]
     },
     "execution_count": 109,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df.head(20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 111,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "'the label [Aberdeen] is not in the [index]'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32mC:\\Users\\feyman\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_has_valid_type\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m   1505\u001b[0m                 \u001b[1;32mif\u001b[0m \u001b[1;32mnot\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcontains\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1506\u001b[0;31m                     \u001b[0merror\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1507\u001b[0m             \u001b[1;32mexcept\u001b[0m \u001b[0mTypeError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Users\\feyman\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36merror\u001b[0;34m()\u001b[0m\n\u001b[1;32m   1500\u001b[0m                                .format(key=key,\n\u001b[0;32m-> 1501\u001b[0;31m                                        axis=self.obj._get_axis_name(axis)))\n\u001b[0m\u001b[1;32m   1502\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'the label [Aberdeen] is not in the [index]'",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-111-8b9f2aba0db5>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnew_df\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;34m'Aberdeen'\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32mC:\\Users\\feyman\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, key)\u001b[0m\n\u001b[1;32m   1371\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m   1372\u001b[0m             \u001b[0mmaybe_callable\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcom\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_apply_if_callable\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mobj\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1373\u001b[0;31m             \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_getitem_axis\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmaybe_callable\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1374\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m   1375\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0m_is_scalar_access\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mkey\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Users\\feyman\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_getitem_axis\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m   1624\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m   1625\u001b[0m         \u001b[1;31m# fall thru to straight lookup\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1626\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_has_valid_type\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1627\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_label\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkey\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0maxis\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0maxis\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m   1628\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Users\\feyman\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36m_has_valid_type\u001b[0;34m(self, key, axis)\u001b[0m\n\u001b[1;32m   1512\u001b[0m                 \u001b[1;32mraise\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m   1513\u001b[0m             \u001b[1;32mexcept\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1514\u001b[0;31m                 \u001b[0merror\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1515\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m   1516\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[1;32mTrue\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mC:\\Users\\feyman\\Anaconda3\\lib\\site-packages\\pandas\\core\\indexing.py\u001b[0m in \u001b[0;36merror\u001b[0;34m()\u001b[0m\n\u001b[1;32m   1499\u001b[0m                 raise KeyError(u\"the label [{key}] is not in the [{axis}]\"\n\u001b[1;32m   1500\u001b[0m                                .format(key=key,\n\u001b[0;32m-> 1501\u001b[0;31m                                        axis=self.obj._get_axis_name(axis)))\n\u001b[0m\u001b[1;32m   1502\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m   1503\u001b[0m             \u001b[1;32mtry\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyError\u001b[0m: 'the label [Aberdeen] is not in the [index]'"
     ]
    }
   ],
   "source": [
    "new_df.loc['Aberdeen']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "可以使用切片(slicers)对多重索引进行操作\n",
    "\n",
    "* 你可以使用任意的列表，元祖，布尔型作为Indexer\n",
    "* 可以使用sclie(None)表达在某个level上选取全部的内容，不需要对全部的level进行指定，它们会被隐式的推导为slice(None)\n",
    "* 所有的axis必须都被指定，意味着index和column上都要被显式的指明\n",
    "* 我们应该对多重索引进行排序"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>Player</th>\n",
       "      <th>height</th>\n",
       "      <th>weight</th>\n",
       "      <th>collage</th>\n",
       "      <th>born</th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "      <th>flag</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>birth_city</th>\n",
       "      <th>birth_state</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <th>Albany</th>\n",
       "      <th>Texas</th>\n",
       "      <td>Chick Halbert</td>\n",
       "      <td>206.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>West Texas A&amp;M University</td>\n",
       "      <td>1919.0</td>\n",
       "      <td>Albany</td>\n",
       "      <td>Texas</td>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>539</th>\n",
       "      <th>Akron</th>\n",
       "      <th>Ohio</th>\n",
       "      <td>Jimmy Darrow</td>\n",
       "      <td>178.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>Bowling Green State University</td>\n",
       "      <td>1937.0</td>\n",
       "      <td>Akron</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>msize</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>609</th>\n",
       "      <th>Akron</th>\n",
       "      <th>Ohio</th>\n",
       "      <td>Gus Johnson*</td>\n",
       "      <td>198.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>University of Idaho</td>\n",
       "      <td>1938.0</td>\n",
       "      <td>Akron</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>620</th>\n",
       "      <th>Akron</th>\n",
       "      <th>Ohio</th>\n",
       "      <td>Nate Thurmond*</td>\n",
       "      <td>211.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>Bowling Green State University</td>\n",
       "      <td>1941.0</td>\n",
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       "      <td>Ohio</td>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>1028</th>\n",
       "      <th>Albany</th>\n",
       "      <th>Georgia</th>\n",
       "      <td>Ben Clyde</td>\n",
       "      <td>201.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>Florida State University</td>\n",
       "      <td>1951.0</td>\n",
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       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>1927</th>\n",
       "      <th>Akron</th>\n",
       "      <th>Ohio</th>\n",
       "      <td>Jerome Lane</td>\n",
       "      <td>198.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>University of Pittsburgh</td>\n",
       "      <td>1966.0</td>\n",
       "      <td>Akron</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2374</th>\n",
       "      <th>Albany</th>\n",
       "      <th>Georgia</th>\n",
       "      <td>Dontonio Wingfield</td>\n",
       "      <td>203.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>University of Cincinnati</td>\n",
       "      <td>1974.0</td>\n",
       "      <td>Albany</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2756</th>\n",
       "      <th>Albany</th>\n",
       "      <th>Georgia</th>\n",
       "      <td>Lavor Postell</td>\n",
       "      <td>196.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>St. John's University</td>\n",
       "      <td>1978.0</td>\n",
       "      <td>Albany</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>high</td>\n",
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       "    <tr>\n",
       "      <th>2882</th>\n",
       "      <th>Akron</th>\n",
       "      <th>Ohio</th>\n",
       "      <td>Chris Owens</td>\n",
       "      <td>201.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>University of Texas at Austin</td>\n",
       "      <td>1979.0</td>\n",
       "      <td>Akron</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2944</th>\n",
       "      <th>Akron</th>\n",
       "      <th>Ohio</th>\n",
       "      <td>LeBron James</td>\n",
       "      <td>203.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>Akron</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2985</th>\n",
       "      <th>Albany</th>\n",
       "      <th>New York</th>\n",
       "      <td>Lionel Chalmers</td>\n",
       "      <td>183.0</td>\n",
       "      <td>81.0</td>\n",
       "      <td>Xavier University</td>\n",
       "      <td>1980.0</td>\n",
       "      <td>Albany</td>\n",
       "      <td>New York</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3163</th>\n",
       "      <th>Albany</th>\n",
       "      <th>Georgia</th>\n",
       "      <td>Alexander Johnson</td>\n",
       "      <td>206.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>Florida State University</td>\n",
       "      <td>1983.0</td>\n",
       "      <td>Albany</td>\n",
       "      <td>Georgia</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3287</th>\n",
       "      <th>Ahvaz</th>\n",
       "      <th>Islamic Republic of Iran</th>\n",
       "      <td>Hamed Haddadi</td>\n",
       "      <td>218.0</td>\n",
       "      <td>115.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>1985.0</td>\n",
       "      <td>Ahvaz</td>\n",
       "      <td>Islamic Republic of Iran</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>3343</th>\n",
       "      <th>Akron</th>\n",
       "      <th>Ohio</th>\n",
       "      <td>Stephen Curry</td>\n",
       "      <td>190.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>Davidson College</td>\n",
       "      <td>1988.0</td>\n",
       "      <td>Akron</td>\n",
       "      <td>Ohio</td>\n",
       "      <td>high</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                      Player  height  weight  \\\n",
       "     birth_city birth_state                                                    \n",
       "71   Albany     Texas                          Chick Halbert   206.0   102.0   \n",
       "539  Akron      Ohio                            Jimmy Darrow   178.0    77.0   \n",
       "609  Akron      Ohio                            Gus Johnson*   198.0   104.0   \n",
       "620  Akron      Ohio                          Nate Thurmond*   211.0   102.0   \n",
       "1028 Albany     Georgia                            Ben Clyde   201.0    89.0   \n",
       "1927 Akron      Ohio                             Jerome Lane   198.0   104.0   \n",
       "2374 Albany     Georgia                   Dontonio Wingfield   203.0   116.0   \n",
       "2756 Albany     Georgia                        Lavor Postell   196.0    97.0   \n",
       "2882 Akron      Ohio                             Chris Owens   201.0   111.0   \n",
       "2944 Akron      Ohio                            LeBron James   203.0   113.0   \n",
       "2985 Albany     New York                     Lionel Chalmers   183.0    81.0   \n",
       "3163 Albany     Georgia                    Alexander Johnson   206.0   108.0   \n",
       "3287 Ahvaz      Islamic Republic of Iran       Hamed Haddadi   218.0   115.0   \n",
       "3343 Akron      Ohio                           Stephen Curry   190.0    86.0   \n",
       "\n",
       "                                                                 collage  \\\n",
       "     birth_city birth_state                                                \n",
       "71   Albany     Texas                          West Texas A&M University   \n",
       "539  Akron      Ohio                      Bowling Green State University   \n",
       "609  Akron      Ohio                                 University of Idaho   \n",
       "620  Akron      Ohio                      Bowling Green State University   \n",
       "1028 Albany     Georgia                         Florida State University   \n",
       "1927 Akron      Ohio                            University of Pittsburgh   \n",
       "2374 Albany     Georgia                         University of Cincinnati   \n",
       "2756 Albany     Georgia                            St. John's University   \n",
       "2882 Akron      Ohio                       University of Texas at Austin   \n",
       "2944 Akron      Ohio                                                 NaN   \n",
       "2985 Albany     New York                               Xavier University   \n",
       "3163 Albany     Georgia                         Florida State University   \n",
       "3287 Ahvaz      Islamic Republic of Iran                             NaN   \n",
       "3343 Akron      Ohio                                    Davidson College   \n",
       "\n",
       "                                            born birth_city  \\\n",
       "     birth_city birth_state                                   \n",
       "71   Albany     Texas                     1919.0     Albany   \n",
       "539  Akron      Ohio                      1937.0      Akron   \n",
       "609  Akron      Ohio                      1938.0      Akron   \n",
       "620  Akron      Ohio                      1941.0      Akron   \n",
       "1028 Albany     Georgia                   1951.0     Albany   \n",
       "1927 Akron      Ohio                      1966.0      Akron   \n",
       "2374 Albany     Georgia                   1974.0     Albany   \n",
       "2756 Albany     Georgia                   1978.0     Albany   \n",
       "2882 Akron      Ohio                      1979.0      Akron   \n",
       "2944 Akron      Ohio                      1984.0      Akron   \n",
       "2985 Albany     New York                  1980.0     Albany   \n",
       "3163 Albany     Georgia                   1983.0     Albany   \n",
       "3287 Ahvaz      Islamic Republic of Iran  1985.0      Ahvaz   \n",
       "3343 Akron      Ohio                      1988.0      Akron   \n",
       "\n",
       "                                                       birth_state   flag  \n",
       "     birth_city birth_state                                                \n",
       "71   Albany     Texas                                        Texas   high  \n",
       "539  Akron      Ohio                                          Ohio  msize  \n",
       "609  Akron      Ohio                                          Ohio   high  \n",
       "620  Akron      Ohio                                          Ohio   high  \n",
       "1028 Albany     Georgia                                    Georgia   high  \n",
       "1927 Akron      Ohio                                          Ohio   high  \n",
       "2374 Albany     Georgia                                    Georgia   high  \n",
       "2756 Albany     Georgia                                    Georgia   high  \n",
       "2882 Akron      Ohio                                          Ohio   high  \n",
       "2944 Akron      Ohio                                          Ohio   high  \n",
       "2985 Albany     New York                                  New York   high  \n",
       "3163 Albany     Georgia                                    Georgia   high  \n",
       "3287 Ahvaz      Islamic Republic of Iran  Islamic Republic of Iran   high  \n",
       "3343 Akron      Ohio                                          Ohio   high  "
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "new_df.loc[(slice(None),['Akron','Ahvaz','Albany'],slice(None)),:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "pandas.core.series.Series"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "type(new_df.loc[(slice(None),['Akron','Ahvaz','Albany'],['Ohio','New York']),\"Player\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "metadata": {},
   "outputs": [
    {
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       "      <th>14</th>\n",
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       "      <td>Freddie Lewis</td>\n",
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       "      <th>113</th>\n",
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       "      <td>Ray Lumpp</td>\n",
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       "      <th>222</th>\n",
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       "      <td>Brendan McCann</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>468</th>\n",
       "      <th>Brooklyn</th>\n",
       "      <th>New York</th>\n",
       "      <td>Pete Brennan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>471</th>\n",
       "      <th>Brooklyn</th>\n",
       "      <th>New York</th>\n",
       "      <td>Connie Dierking</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                     Player\n",
       "    birth_city birth_state                 \n",
       "11  Brooklyn   New York       Harry Boykoff\n",
       "14  Brooklyn   New York          Carl Braun\n",
       "53  Brooklyn   New York     Jerry Fleishman\n",
       "83  Brooklyn   New York     Sonny Hertzberg\n",
       "86  Brooklyn   New York        Red Holzman*\n",
       "109 Brooklyn   New York       Andrew Levane\n",
       "110 Brooklyn   New York       Freddie Lewis\n",
       "113 Brooklyn   New York           Ray Lumpp\n",
       "218 Brooklyn   New York       Bobby Wanzer*\n",
       "222 Brooklyn   New York       Max Zaslofsky\n",
       "286 Brooklyn   New York          Jim Brasco\n",
       "318 Brooklyn   New York        Zeke Zawoluk\n",
       "455 Brooklyn   New York      Brendan McCann\n",
       "468 Brooklyn   New York        Pete Brennan\n",
       "471 Brooklyn   New York     Connie Dierking"
      ]
     },
     "execution_count": 121,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# IndexSlice是一种更接近自然语法的用法，可以替换slice\n",
    "idx = pd.IndexSlice\n",
    "\n",
    "new_df.loc[idx[0:500,['Brooklyn'],['Ohio','New York']],:idx[\"Player\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 122,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "?new_df.reset_index"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 分组计算\n",
    "\n",
    "By “group by” we are referring to a process involving one or more of the following steps\n",
    "\n",
    "* **Splitting** the data into groups based on some criteria\n",
    "* **Applying** a function to each group independently\n",
    "* **Combining** the results into a data structure\n",
    "Of these, the split step is the most straightforward. In fact, in many situations you may wish to split the data set into groups and do something with those groups yourself. In the apply step, we might wish to one of the following:\n",
    "\n",
    "\n",
    "* **Aggregation**: computing a summary statistic (or statistics) about each group. Some examples:\n",
    "\n",
    "    * Compute group sums or means\n",
    "    * Compute group sizes / counts\n",
    "    \n",
    "* **Transformation**: perform some group-specific computations and return a like-indexed. Some examples:\n",
    "\n",
    "    * Standardizing data (zscore) within group\n",
    "    * Filling NAs within groups with a value derived from each group\n",
    "    \n",
    "* **Filtration**: discard some groups, according to a group-wise computation that evaluates True or False. Some examples:\n",
    "\n",
    "    * Discarding data that belongs to groups with only a few members\n",
    "    * Filtering out data based on the group sum or mean\n",
    "    \n",
    "Some combination of the above: GroupBy will examine the results of the apply step and try to return a sensibly combined result if it doesn’t fit into either of the above two categories\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "* _类似于SQL里面的group by 语句，不过pandas提供了更加复杂的函数方法_\n",
    "\n",
    "* _我们可以对index或者column进行分组，可以被一个元素，也可以是任意多个元素分组。分组后计算的方式否是一样的，无论是基于index还是column._"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>color</th>\n",
       "      <th>director_name</th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>duration</th>\n",
       "      <th>director_facebook_likes</th>\n",
       "      <th>actor_3_facebook_likes</th>\n",
       "      <th>actor_2_name</th>\n",
       "      <th>actor_1_facebook_likes</th>\n",
       "      <th>gross</th>\n",
       "      <th>genres</th>\n",
       "      <th>...</th>\n",
       "      <th>num_user_for_reviews</th>\n",
       "      <th>language</th>\n",
       "      <th>country</th>\n",
       "      <th>content_rating</th>\n",
       "      <th>budget</th>\n",
       "      <th>title_year</th>\n",
       "      <th>actor_2_facebook_likes</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Color</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>723.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>855.0</td>\n",
       "      <td>Joel David Moore</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>760505847.0</td>\n",
       "      <td>Action|Adventure|Fantasy|Sci-Fi</td>\n",
       "      <td>...</td>\n",
       "      <td>3054.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>237000000.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>7.9</td>\n",
       "      <td>1.78</td>\n",
       "      <td>33000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Color</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "      <td>302.0</td>\n",
       "      <td>169.0</td>\n",
       "      <td>563.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>Orlando Bloom</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>309404152.0</td>\n",
       "      <td>Action|Adventure|Fantasy</td>\n",
       "      <td>...</td>\n",
       "      <td>1238.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>300000000.0</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Color</td>\n",
       "      <td>Sam Mendes</td>\n",
       "      <td>602.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>Rory Kinnear</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>200074175.0</td>\n",
       "      <td>Action|Adventure|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>994.0</td>\n",
       "      <td>English</td>\n",
       "      <td>UK</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>245000000.0</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>393.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.35</td>\n",
       "      <td>85000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Color</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "      <td>813.0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>22000.0</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>Christian Bale</td>\n",
       "      <td>27000.0</td>\n",
       "      <td>448130642.0</td>\n",
       "      <td>Action|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>2701.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>250000000.0</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>8.5</td>\n",
       "      <td>2.35</td>\n",
       "      <td>164000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Doug Walker</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>131.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rob Walker</td>\n",
       "      <td>131.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Documentary</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   color      director_name  num_critic_for_reviews  duration  \\\n",
       "0  Color      James Cameron                   723.0     178.0   \n",
       "1  Color     Gore Verbinski                   302.0     169.0   \n",
       "2  Color         Sam Mendes                   602.0     148.0   \n",
       "3  Color  Christopher Nolan                   813.0     164.0   \n",
       "4    NaN        Doug Walker                     NaN       NaN   \n",
       "\n",
       "   director_facebook_likes  actor_3_facebook_likes      actor_2_name  \\\n",
       "0                      0.0                   855.0  Joel David Moore   \n",
       "1                    563.0                  1000.0     Orlando Bloom   \n",
       "2                      0.0                   161.0      Rory Kinnear   \n",
       "3                  22000.0                 23000.0    Christian Bale   \n",
       "4                    131.0                     NaN        Rob Walker   \n",
       "\n",
       "   actor_1_facebook_likes        gross                           genres  \\\n",
       "0                  1000.0  760505847.0  Action|Adventure|Fantasy|Sci-Fi   \n",
       "1                 40000.0  309404152.0         Action|Adventure|Fantasy   \n",
       "2                 11000.0  200074175.0        Action|Adventure|Thriller   \n",
       "3                 27000.0  448130642.0                  Action|Thriller   \n",
       "4                   131.0          NaN                      Documentary   \n",
       "\n",
       "          ...          num_user_for_reviews language  country  content_rating  \\\n",
       "0         ...                        3054.0  English      USA           PG-13   \n",
       "1         ...                        1238.0  English      USA           PG-13   \n",
       "2         ...                         994.0  English       UK           PG-13   \n",
       "3         ...                        2701.0  English      USA           PG-13   \n",
       "4         ...                           NaN      NaN      NaN             NaN   \n",
       "\n",
       "        budget  title_year actor_2_facebook_likes imdb_score  aspect_ratio  \\\n",
       "0  237000000.0      2009.0                  936.0        7.9          1.78   \n",
       "1  300000000.0      2007.0                 5000.0        7.1          2.35   \n",
       "2  245000000.0      2015.0                  393.0        6.8          2.35   \n",
       "3  250000000.0      2012.0                23000.0        8.5          2.35   \n",
       "4          NaN         NaN                   12.0        7.1           NaN   \n",
       "\n",
       "  movie_facebook_likes  \n",
       "0                33000  \n",
       "1                    0  \n",
       "2                85000  \n",
       "3               164000  \n",
       "4                    0  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 123,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"movie.csv\")\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Steven Spielberg        26\n",
       "Woody Allen             22\n",
       "Clint Eastwood          20\n",
       "Martin Scorsese         20\n",
       "Ridley Scott            17\n",
       "Tim Burton              16\n",
       "Steven Soderbergh       16\n",
       "Spike Lee               16\n",
       "Renny Harlin            15\n",
       "Oliver Stone            14\n",
       "Sam Raimi               13\n",
       "Barry Levinson          13\n",
       "John Carpenter          13\n",
       "Robert Rodriguez        13\n",
       "Ron Howard              13\n",
       "Robert Zemeckis         13\n",
       "Michael Bay             13\n",
       "Joel Schumacher         13\n",
       "Richard Donner          12\n",
       "Tony Scott              12\n",
       "Peter Jackson           12\n",
       "Brian De Palma          12\n",
       "Wes Craven              12\n",
       "Shawn Levy              12\n",
       "Kevin Smith             12\n",
       "Rob Reiner              11\n",
       "Chris Columbus          11\n",
       "Rob Cohen               11\n",
       "Stephen Frears          11\n",
       "Francis Ford Coppola    11\n",
       "                        ..\n",
       "Scott Dow                1\n",
       "Jason Naumann            1\n",
       "Michael Winnick          1\n",
       "Louis C.K.               1\n",
       "Robert Stromberg         1\n",
       "Ryûhei Kitamura          1\n",
       "Paul Mazursky            1\n",
       "Eric Eason               1\n",
       "Kirsten Sheridan         1\n",
       "William Phillips         1\n",
       "Avi Nesher               1\n",
       "Liz Friedlander          1\n",
       "Jeta Amata               1\n",
       "Lance Hool               1\n",
       "Måns Mårlind             1\n",
       "Matthew O'Callaghan      1\n",
       "Sacha Bennett            1\n",
       "Martin Weisz             1\n",
       "Hunter Richards          1\n",
       "Mike Gabriel             1\n",
       "Rakesh Roshan            1\n",
       "Henry Jaglom             1\n",
       "Ronan Chapalain          1\n",
       "Andrea Di Stefano        1\n",
       "Kyle Balda               1\n",
       "David Cross              1\n",
       "Stanley Donen            1\n",
       "Linda Mendoza            1\n",
       "Nathan Greno             1\n",
       "Gene Teigland            1\n",
       "Name: director_name, Length: 2398, dtype: int64"
      ]
     },
     "execution_count": 125,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.director_name.value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 127,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "grouped = df.groupby(\"director_name\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 128,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<pandas.core.groupby.DataFrameGroupBy object at 0x000001E6D6FF72E8>"
      ]
     },
     "execution_count": 128,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 132,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2398"
      ]
     },
     "execution_count": 132,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped.size()\n",
    "grouped.groups\n",
    "len(grouped)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 134,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "A. Raven Cruz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Aaron Hann\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Aaron Schneider\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Aaron Seltzer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Abel Ferrara\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Adam Brooks\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Adam Carolla\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Adam Goldberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Adam Green\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Adam Jay Epstein\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Adam Marcus\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Adam McKay\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Adam Rapp\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Adam Rifkin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Adam Shankman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Adrian Lyne\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Adrienne Shelly\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Agnieszka Holland\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Agnieszka Wojtowicz-Vosloo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Agustín Díaz Yanes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Aki Kaurismäki\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Akira Kurosawa\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Akiva Goldsman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Akiva Schaffer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Al Franklin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Al Silliman Jr.\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alain Resnais\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alan Alda\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alan Cohn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alan J. Pakula\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alan Jacobs\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alan Metter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alan Parker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alan Poul\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alan Rudolph\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alan Shapiro\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alan Taylor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alan Yuen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Albert Brooks\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Albert Hughes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alec Asten\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alejandro Agresti\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alejandro Amenábar\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alejandro G. Iñárritu\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alejandro Monteverde\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Aleksandr Veledinskiy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Aleksey German\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alessandro Carloni\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alex Cox\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alex Craig Mann\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alex Garland\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alex Gibney\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alex Kendrick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alex Proyas\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alex Ranarivelo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alex Rivera\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alex Smith\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alex Zamm\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alex van Warmerdam\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alexander Payne\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alexander Witt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alexandre Aja\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alfonso Cuarón\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alfred Hitchcock\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alice Wu\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alison Maclean\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Alister Grierson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Allan Arkush\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Allan Dwan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Allen Coulter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Allen Hughes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Allison Anders\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Allison Burnett\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Amal Al-Agroobi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Amanda Gusack\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Amat Escalante\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Amy Heckerling\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Amy Holden Jones\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Analeine Cal y Mayor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anand Tucker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrea Arnold\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrea Di Stefano\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrei Tarkovsky\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Adamson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Berends\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Bergman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Bujalski\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Currie\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Davis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Dominik\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Douglas\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Erwin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Fleming\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Haigh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Hyatt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Jarecki\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Leman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Morahan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Niccol\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Stanton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Steggall\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Traucki\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrew Wilson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrey Konchalovskiy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrey Zvyagintsev\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrucha Waddington\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrzej Bartkowiak\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "André Téchiné\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "André Øvredal\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrés Couturier\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andrés Muschietti\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andy Cadiff\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andy Fickman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andy Garcia\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Andy Tennant\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ang Lee\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Angela Robinson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Angelina Jolie Pitt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Angelo Pizzo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anna Boden\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anna Mastro\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anna Muylaert\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Annabel Jankel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anne Fletcher\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anne Fontaine\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anthony Bell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anthony C. Ferrante\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anthony Hemingway\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anthony Hickox\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anthony Mann\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anthony Minghella\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anthony O'Brien\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anthony Powell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anthony Russo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anthony Silverston\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anthony Vallone\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Antoine Fuqua\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anton Corbijn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Antonia Bird\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Antonio Banderas\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Antonio Simoncini\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Antony Hoffman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Anurag Basu\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ari Folman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ari Kirschenbaum\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ari Sandel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Arie Posin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ariel Vromen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Arjun Sablok\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Arthur Hiller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Asger Leth\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Asghar Farhadi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ash Baron-Cohen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ash Brannon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ashish R. Mohan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Atom Egoyan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Audrey Wells\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ava DuVernay\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Avi Nesher\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ayan Mukerji\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Babak Najafi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Babar Ahmed\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Baltasar Kormákur\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Barbet Schroeder\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Barbra Streisand\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Barrett Esposito\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Barry Cook\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Barry Levinson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Barry Skolnick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Barry Sonnenfeld\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Barry W. Blaustein\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bart Freundlich\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Baz Luhrmann\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Becky Smith\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Beeban Kidron\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ben Affleck\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ben Falcone\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ben Lewin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ben Stassen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ben Stiller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ben Wheatley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ben Younger\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Benedek Fliegauf\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Benedikt Erlingsson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Benh Zeitlin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Benjamin Dickinson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Benjamin Roberds\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bennett Miller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Benni Diez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Benny Boom\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Benson Lee\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bernardo Bertolucci\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Beto Gómez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Betty Thomas\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bibo Bergeron\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bigas Luna\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bill Benenson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bill Condon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bill Duke\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bill Melendez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bill Muir\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bill Paxton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bill Plympton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bille August\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bille Woodruff\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Billy Bob Thornton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Billy Kent\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Billy Ray\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Billy Wilder\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Blair Erickson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Blair Hayes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Blake Edwards\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Blaz Zavrsnik\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bo Welch\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bo Zenga\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Boaz Yakin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bob Clark\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bob Dolman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bob Fosse\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bob Giraldi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bob Gosse\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bob Odenkirk\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bob Rafelson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bob Saget\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bob Spiers\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bobby Farrelly\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bobby Roth\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bobcat Goldthwait\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bonnie Hunt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Boris Rodriguez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brad Anderson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brad Bird\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brad Copeland\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brad Furman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brad J. Silverman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brad Peyton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brad Silberling\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bradley Parker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bradley Rust Gray\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brandon Camp\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brandon Cronenberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brandon Landers\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brandon Trost\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Breck Eisner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brenda Chapman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brendan Malloy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brenton Spencer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brett Leonard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brett Piper\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brett Ratner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brian A Miller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brian Baugh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brian Caunter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brian Dannelly\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brian De Palma\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brian Dorton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brian Gibson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brian Helgeland\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brian Henson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brian Klugman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brian Koppelman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brian Levant\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brian Percival\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brian Robbins\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brian Trenchard-Smith\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Brian Yuzna\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Britt Allcroft\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bronwen Hughes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bruce Beresford\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bruce Campbell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bruce Dellis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bruce Hunt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bruce Macdonald\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bruce Malmuth\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bruce McCulloch\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bruce McDonald\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bruce Paltrow\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bruno Barreto\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bryan Barber\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Bryan Singer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Burr Steers\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Byron Howard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "C. Fraser Press\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "C. Jay Cox\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Cal Brunker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Callie Khouri\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Cameron Crowe\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Camille Delamarre\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Carl Franklin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Carl Rinsch\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Carl Theodor Dreyer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Carlos Carrera\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Carlos Saldanha\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Carlos Saura\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Carmen Marron\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Carol Reed\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Caroline Link\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Carroll Ballard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Carter Smith\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Cary Bell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Caryn Waechter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Cassandra Nicolaou\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Catherine Gund\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Catherine Hardwicke\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Catherine Jelski\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Catherine Owens\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Cathy Malkasian\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Cecil B. DeMille\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Cedric Nicolas-Troyan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chad Hartigan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chad Kapper\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chan-wook Park\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chao-Bin Su\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Charles Adelman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Charles Binamé\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Charles Chaplin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Charles Ferguson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Charles Herman-Wurmfeld\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Charles Martin Smith\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Charles Matthau\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Charles Robert Carner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Charles S. Dutton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Charles Shyer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Charles Stone III\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Charles T. Kanganis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Charlie Kaufman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Charlie Levi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chatrichalerm Yukol\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Cheryl Dunye\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chia-Liang Liu\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Atkins\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Buck\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Butler\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Carter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Columbus\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris D'Arienzo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Eyre\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Gorak\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Kentis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Koch\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Marker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Miller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Nahon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Noonan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Paine\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Roberts\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Robinson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Rock\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Shadley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Stokes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Wedge\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chris Weitz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christian Alvart\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christian Carion\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christian Ditter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christian Duguay\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christian E. Christiansen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christian Sesma\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christian Volckman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christine Jeffs\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christophe Ali\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christophe Barratier\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christophe Gans\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christopher Barnard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christopher Cain\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christopher Erskin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christopher Guest\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christopher Hutson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christopher Landon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christopher Leitch\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christopher M. Bessette\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christopher McQuarrie\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christopher Morris\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christopher Nolan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christopher Scott Cherot\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christopher Smith\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Christopher Spencer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chuan Lu\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chuck Bowman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chuck Russell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Chuck Sheetz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ciarán Foy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Clare Kilner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Clark Baker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Clark Gregg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Clark Johnson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Claude Chabrol\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Claude Miller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Claudia Llosa\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Claudia Sainte-Luce\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Clay Kaytis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Clint Eastwood\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Clive Barker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Cody Cameron\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Colin Higgins\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Colin Minihan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Colin Strause\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Colin Trevorrow\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Collin Joseph Neal\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Collin Schiffli\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Conor McMahon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Conor McPherson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Corbin Bernsen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Corey Grant\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Corey Yuen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Cory Edwards\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Costa-Gavras\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Courtney Hunt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Courtney Solomon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Craig Bolotin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Craig Brewer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Craig Gillespie\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Craig Johnson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Craig Mazin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Craig Moss\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Craig R. Baxley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Craig Zobel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Cristian Mungiu\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Curtis Hanson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Cyrus Nowrasteh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Cédric Klapisch\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "D. Stevens\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "D.J. Caruso\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "D.W. Griffith\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "DJ Pooh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dagur Kári\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daisy von Scherler Mayer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Damian Nieman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Damien Chazelle\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Damien Dante Wayans\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Damien O'Donnell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Damir Catic\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Damon Santostefano\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dan Curtis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dan Cutforth\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dan Fogelman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dan Gilroy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dan Harris\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dan Ireland\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dan Mazer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dan O'Bannon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dan Perri\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dan Reed\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dan Rush\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dan Scanlon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dan Trachtenberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dan Zukovic\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daniel Algrant\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daniel Barber\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daniel Barnz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daniel Columbie\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daniel Davila\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daniel Espinosa\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daniel Hsia\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daniel Lee\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daniel Mellitz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daniel Myrick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daniel Petrie Jr.\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daniel Sackheim\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daniel Schechter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daniel Stamm\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daniel Taplitz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daniele Luchetti\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Danny Boyle\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Danny Cannon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Danny DeVito\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Danny Leiner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Danny Pang\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Danny Perez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Danny Provenzano\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Danny Steinmann\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dany Boon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Darin Scott\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dario Argento\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Darnell Martin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Darrell Roodt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Darren Aronofsky\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Darren Grant\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Darren Lynn Bousman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Darren Stein\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daryl Wein\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Daston Kalili\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dave Borthwick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dave Carroll\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dave Green\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dave McKean\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dave Meyers\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dave Payne\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dave Rodriguez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Anspaugh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Atkins\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Ayer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Bowers\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Boyd\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Caffrey\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Carson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Cronenberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Cross\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David DeCoteau\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Dobkin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Duchovny\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David E. Talbert\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David F. Sandberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Fincher\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Frankel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David G. Evans\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Gelb\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Gordon Green\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Hackl\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Hayter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Hewlett\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Hunt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Jacobson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Kellogg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Koepp\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David LaChapelle\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Lam\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Lean\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Leland\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Lowery\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Lynch\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David M. Matthews\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Mamet\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David McNally\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Mirkin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Moreau\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Nixon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Nutter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David O. Russell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Oelhoffen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Palmer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Pastor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David R. Ellis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Ray\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Raynr\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Robert Mitchell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David S. Goyer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David S. Ward\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Schwimmer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Silverman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Sington\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Slade\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Soren\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Twohy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Wain\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Webb Peoples\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Winning\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Winters\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Worth\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Yates\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "David Zucker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Davis Guggenheim\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dean DeBlois\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dean Israelite\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dean Parisot\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dean Wright\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Deb Hagan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Deborah Anderson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Debra Granik\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Deepa Mehta\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Demian Lichtenstein\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dena Seidel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Denis Villeneuve\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dennie Gordon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dennis Dugan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dennis Gansel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dennis Hopper\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dennis Iliadis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Denys Arcand\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Denzel Washington\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Deon Taylor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Derek Cianfrance\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Derick Martini\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Derrick Borte\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Deryck Broom\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Des McAnuff\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dewey Nicks\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dexter Fletcher\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Diane English\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Diane Keaton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dick Richards\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dinesh D'Souza\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dito Montiel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dominic Burns\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dominic Sena\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dominique Othenin-Girard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Don Bluth\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Don Coscarelli\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Don Hall\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Don Kempf\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Don Mancini\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Don Michael Paul\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Don Scardino\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Don Siegel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Don Taylor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Donald Petrie\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Doug Atchison\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Doug Block\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Doug Lefler\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Doug Liman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Doug Walker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Douglas Aarniokoski\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Douglas Cheek\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Douglas McGrath\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Douglas Trumbull\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Drake Doremus\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Drew Barrymore\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Drew Goddard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dror Moreh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Duane Journey\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Duke Johnson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Duncan Jones\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Duncan Tucker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dustin Hoffman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dwight H. Little\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Dylan Bank\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "E. Elias Merhige\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "E.L. Katz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ed Decter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ed Gass-Donnelly\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ed Harris\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eddie O'Flaherty\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Edgar Wright\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Edward Burns\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Edward Dmytryk\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Edward Hall\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Edward Norton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Edward Zwick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Efram Potelle\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ekachai Uekrongtham\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Elaine May\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eldar Rapaport\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eli Craig\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eli Roth\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Elia Kazan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Elizabeth Allen Rosenbaum\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Elizabeth Banks\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ellory Elkayem\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Emile Ardolino\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Emilio Estevez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Emily Dell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Emily Young\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Emma-Kate Croghan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Enrique Begne\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eric Blakeney\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eric Bress\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eric Brevig\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eric Bross\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eric Bugbee\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eric Darnell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eric Eason\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eric England\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eric Lartigau\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eric Lavaine\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eric Leighton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eric Mendelsohn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eric Nicholas\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eric Schaeffer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eric Styles\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eric Valette\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ericson Core\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Erik Canuel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Erik White\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ernest R. Dickerson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ernie Barbarash\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Errol Morris\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Etan Cohen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ethan Coen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ethan Maniquis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eugenio Derbez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eugène Lourié\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Evan Goldberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Eytan Fox\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "F. Gary Gray\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fabián Bielinsky\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fatih Akin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fede Alvarez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fedor Bondarchuk\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fenton Bailey\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fernando Baez Mella\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fernando León de Aranoa\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fernando Meirelles\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Feroz Abbas Khan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ferzan Ozpetek\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fina Torres\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Finn Taylor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Florence Ayisi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Florent-Emilio Siri\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Floria Sigismondi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Florian Henckel von Donnersmarck\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Floyd Mutrux\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Forest Whitaker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Francesca Gregorini\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Francis Ford Coppola\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Francis Lawrence\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Franck Khalfoun\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Franco Zeffirelli\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Frank Borzage\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Frank Capra\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Frank Coraci\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Frank Darabont\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Frank LaLoggia\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Frank Lotito\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Frank Marshall\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Frank Miller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Frank Nissen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Frank Oz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Frank Perry\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Frank Sebastiano\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Frank Whaley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Franklin J. Schaffner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "François Girard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "François Ozon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "François Truffaut\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fred Dekker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fred Durst\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fred Savage\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fred Schepisi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fred Walton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fred Wolf\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fred Zinnemann\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Frederik Du Chau\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Fritz Lang\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Frédéric Auburtin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Frédéric Forestier\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gabe Ibáñez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gabor Csupo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gabriela Tagliavini\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gabriele Muccino\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gareth Edwards\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gareth Evans\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Garry Marshall\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Garth Jennings\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gary Chapman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gary David Goldberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gary Fleder\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gary Halvorson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gary Hardwick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gary McKendry\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gary Nelson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gary Rogers\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gary Ross\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gary Sherman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gary Shore\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gary Sinyor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gary Trousdale\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gary Winick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gaspar Noé\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gavin Hood\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gavin O'Connor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gavin Wiesen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gene Quintano\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gene Teigland\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Genndy Tartakovsky\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Geoff Murphy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Geoffrey Sax\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Georg Wilhelm Pabst\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "George A. Romero\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "George Armitage\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "George Clooney\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "George Cukor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "George Gallo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "George Hickenlooper\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "George Jackson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "George Lucas\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "George Miller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "George Nolfi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "George P. Cosmatos\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "George Ratliff\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "George Roy Hill\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "George Sidney\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "George Stevens\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "George Tillman Jr.\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Georgia Hilton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gerald Potterton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gerard Johnstone\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gerry Lively\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gia Coppola\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gideon Raff\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gil Junger\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gil Kenan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gilles Paquet-Brenner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gillian Armstrong\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gillian Robespierre\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gina Prince-Bythewood\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Giovanni Zelko\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Giuliano Montaldo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Giuseppe Tornatore\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Glen Morgan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Glenn Ficarra\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gnana Rajasekaran\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gonzalo López-Gallego\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Goran Dukic\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gordon Chan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gore Verbinski\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Graham Annable\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Grant Heslov\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Greg Berlanti\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Greg Coolidge\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Greg Harrison\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Greg Marcks\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Greg Mottola\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Greg Tiernan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gregor Jordan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gregory Hoblit\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gregory Jacobs\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gregory Nava\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gregory Poirier\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gregory Widen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Griffin Dunne\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Guillaume Canet\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Guillaume Ivernel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Guillermo del Toro\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gurinder Chadha\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gus Van Sant\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Guy Hamilton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Guy Maddin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Guy Ritchie\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Gérard Krawczyk\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "H.M. Coakley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hal Haberman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hal Needham\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ham Tran\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hank Braxtan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hans Canosa\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hans Petter Moland\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hao Ning\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Harald Reinl\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Harald Zwart\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hark Tsui\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Harley Cokeliss\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Harmage Singh Kalirai\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Harmony Korine\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Harold Becker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Harold Cronk\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Harold Ramis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Harry Beaumont\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Harry Elfont\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Harry F. Millarde\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Harry Gantz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hart Bochner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hayao Miyazaki\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hayley Cloake\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Heidi Ewing\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Henry Alex Rubin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Henry Bean\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Henry Hathaway\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Henry Hobson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Henry Jaglom\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Henry Joost\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Henry King\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Henry Koster\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Henry Selick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Herb Freed\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Herbert Ross\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hideaki Anno\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hideo Nakata\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hilary Brougher\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hironobu Sakaguchi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hitoshi Matsumoto\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hong-jin Na\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Howard Deutch\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Howard Hawks\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Howard Hughes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Howard Zieff\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hoyt Yeatman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hsiao-Hsien Hou\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Huck Botko\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hue Rhodes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hugh Hudson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hugh Johnson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hugh Wilson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hunter Richards\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Hyung-rae Shim\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Iain Softley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ian Fitzgibbon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ian Iqbal Rashid\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ian Sharp\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ice Cube\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Igor Kovalyov\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ingmar Bergman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Inna Evlannikova\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ira Sachs\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Irvin Kershner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Irwin Winkler\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Isaac Florentine\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Isabel Coixet\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "István Szabó\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ivan Engler\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ivan Kavanagh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ivan Reitman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "J Blakeson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "J. Lee Thompson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "J.A. Bayona\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "J.B. Rogers\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "J.C. Chandor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "J.J. Abrams\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "J.S. Cardone\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "JK Youn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jack Conway\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jack Heller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jack Perez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jack Sholder\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jack Smight\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jackie Earle Haley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jaco Booyens\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jacob Aaron Estes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jacques Perrin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jafar Panahi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jaime Zevallos\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jake Goldberger\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jake Kasdan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jake Paltrow\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jake Schreier\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jake Scott\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jamaa Fanaka\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jamal Hill\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jamel Debbouze\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Algar\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Bidgood\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Bobin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Bridges\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Cameron\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Cox\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James David Pasternak\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James DeMonaco\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Dodson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Fargo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Foley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Frawley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Gartner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Gray\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Gunn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Isaac\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Ivory\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Kerwin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James L. Brooks\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Manera\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Mangold\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Marsh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Mather\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James McTeigue\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Melkonian\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Mottern\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Nunn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James O'Brien\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Ponsoldt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Schamus\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Toback\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Wan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Watkins\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "James Wong\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jamie Babbit\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jamie Blanks\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jamie Thraves\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jamie Travis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jamin Winans\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jan de Bont\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jane Campion\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jane Clark\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Janusz Kaminski\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jared Hess\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jason Alexander\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jason Bateman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jason Connery\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jason Eisener\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jason Friedberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jason Miller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jason Moore\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jason Naumann\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jason Reitman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jason Stone\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jason Trost\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jason Zada\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jaume Balagueró\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jaume Collet-Serra\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jay Alaimo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jay Chandrasekhar\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jay Duplass\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jay Levey\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jay Oliva\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jay Roach\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jay Russell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Je-kyu Kang\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jean-François Richet\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jean-Jacques Annaud\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jean-Jacques Mantello\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jean-Luc Godard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jean-Marc Vallée\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jean-Marie Poiré\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jean-Paul Rappeneau\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jean-Pierre Jeunet\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeannot Szwarc\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeb Stuart\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jee-woon Kim\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeff Burr\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeff Crook\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeff Franklin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeff Garlin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeff Kanew\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeff Lowell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeff Nathanson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeff Nichols\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeff Schaffer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeff Tremaine\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeff Wadlow\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeffrey St. Jules\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeffrey W. Byrd\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jehane Noujaim\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jem Cohen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jennifer Finnigan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jennifer Flackett\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jennifer Wynne Farmer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jennifer Yuh Nelson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeremy Brock\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeremy Degruson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeremy Leven\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeremy Saulnier\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeremy Sims\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jerome Elston Scott\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jerome Robbins\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jerry Belson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jerry Dugan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jerry Jameson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jerry Rees\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jerry Zaks\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jerry Zucker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jesse Dylan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jesse Peretz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jesse Vaughan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jessica Bendinger\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jessie Nelson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jessy Terrero\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jeta Amata\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jez Butterworth\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jill Sprecher\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jim Abrahams\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jim Amatulli\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jim Chuchu\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jim Fall\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jim Field Smith\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jim Gillespie\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jim Goddard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jim Hanon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jim Issa\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jim Jarmusch\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jim Mickle\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jim Sheridan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jim Sonzero\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jimmy Hayward\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jirí Menzel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joachim Rønning\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joan Chen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joby Harold\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jodie Foster\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jody Hill\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joe Berlinger\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joe Camp\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joe Carnahan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joe Chappelle\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joe Charbanic\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joe Cornish\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joe Cross\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joe Dante\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joe Johnston\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joe Kenemore\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joe Marino\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joe Nussbaum\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joe Pytka\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joe Roth\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joe Swanberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joe Wright\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joel Anderson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joel Coen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joel Edgerton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joel Gallen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joel Paul Reisig\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joel Schumacher\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joel Zwick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joey Lauren Adams\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Johanna Schwartz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John 'Bud' Cardos\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John A. Davis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Badham\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Blanchard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Bonito\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Boorman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Cameron Mitchell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Carl Buechler\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Carney\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Carpenter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Cornell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Cromwell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Crowley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Curran\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John D. Hancock\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Dahl\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Duigan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Eng\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Erick Dowdle\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Ford\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Fortenberry\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Francis Daley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Frankenheimer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John G. Avildsen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Gatins\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Glen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Gray\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Guillermin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Gulager\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John H. Lee\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Hamburg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Herzfeld\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Hillcoat\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Hoffman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Huston\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Lafia\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Laing\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Landis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Lasseter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Lee Hancock\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Luessenhop\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Maclean\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Madden\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Maybury\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John McNaughton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John McTiernan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Michael McDonagh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Milius\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Moore\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Murlowski\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Ottman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Pasquin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Patrick Shanley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Polson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Putch\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John R. Leonetti\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Reinhardt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Sayles\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Schlesinger\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Schultz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Simpson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Singleton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Stainton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Stephenson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Stockwell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Sturges\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Turturro\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Waters\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Wells\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Whitesell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "John Woo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Johnnie To\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Johnny Remo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jon Amiel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jon Avnet\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jon Cassar\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jon Favreau\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jon Gunn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jon Hess\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jon Hurwitz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jon Kasdan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jon Knautz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jon Lucas\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jon M. Chu\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jon Poll\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jon Shear\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jon Stewart\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jon Turteltaub\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jon Wright\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonas Elmer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonas Åkerlund\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Caouette\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Dayton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Demme\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan English\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Frakes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Glazer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Hensleigh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Jakubowicz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Kaplan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Kesselman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Levine\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Liebesman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Lynn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Meyers\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Mostow\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Newman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Parker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Teplitzky\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jonathan Wacks\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joon-ho Bong\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jorge Blanco\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jorge Gaggero\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jorge R. Gutiérrez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jorge Ramírez Suárez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jorma Taccone\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Josef Rusnak\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joseph Dorman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joseph Gordon-Levitt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joseph Green\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joseph Kahn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joseph Kosinski\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joseph L. Mankiewicz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joseph Mazzella\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joseph Ruben\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joseph Sargent\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joseph Zito\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Josh Boone\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Josh Gordon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Josh Schwartz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Josh Trank\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joshua Logan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joshua Marston\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joshua Michael Stern\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joshua Oppenheimer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joshua Seftel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joshua Tickell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Joss Whedon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "José Luis Valenzuela\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "José Padilha\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Juan Carlos Fresnadillo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Juan José Campanella\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Judd Apatow\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jugal Hansraj\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Julian Gilbey\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Julian Jarrold\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Julian Schnabel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Julie Anne Robinson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Julie Davis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Julie Taymor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Julien Temple\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Julio DePietro\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jun Falkenstein\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Juraj Jakubisko\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Justin Chadwick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Justin Dillon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Justin Kerrigan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Justin Lin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Justin Molotnikov\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Justin Paul Miller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Justin Thomas Ostensen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Justin Tipping\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Justin Zackham\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jérôme Deschamps\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Jérôme Salle\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "K. King\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kabir Sadanand\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kaige Chen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kar-Wai Wong\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Karan Johar\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Karen Moncrieff\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Karey Kirkpatrick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kari Skogland\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Karim Aïnouz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Karyn Kusama\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kasi Lemmons\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kat Coiro\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kate Barker-Froyland\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kate Connor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Katherine Brooks\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Katherine Dieckmann\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kathryn Bigelow\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Katie Aselton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Katja von Garnier\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Katsuhiro Ôtomo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Katt Shea\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kay Pollak\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Keenen Ivory Wayans\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Keith Gordon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Keith Parmer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kelly Asbury\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kelly Makin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kelly Reichardt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ken Annakin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ken Del Conte\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ken Kwapis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ken Loach\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ken Roht\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ken Scott\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ken Shapiro\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kenneth Branagh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kenneth Johnson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kenneth Lonergan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kenny Ortega\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kent Alterman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kerry Conran\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Allen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Bray\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Brodie\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Carraway\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Costner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Donovan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Greutert\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Hamedani\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Hooks\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Jordan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Lima\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Macdonald\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Munroe\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Reynolds\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Rodney Sullivan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Smith\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Spacey\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Tancharoen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kevin Tenney\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Khalid Mohamed\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Khalil Sullins\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Khyentse Norbu\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kief Davidson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kim Farrant\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kim Nguyen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kimberly Peirce\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kimble Rendall\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "King Vidor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kinka Usher\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kirk De Micco\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kirk Jones\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kirk Loudon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kirk Wong\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kirsten Sheridan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kiyoshi Kurosawa\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Klaus Menzel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kris Isacsson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kristin Rizzo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kriv Stenders\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kundan Shah\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kunihiko Yuyama\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kurt Hale\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kurt Voss\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kurt Wimmer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Kyle Balda\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lajos Koltai\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lana Wachowski\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lance Hool\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lance Kawas\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lance McDaniel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lance Mungia\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lance Rivera\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Larry Blamire\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Larry Charles\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Larry Clark\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lars von Trier\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Laslo Benedek\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lasse Hallström\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lauren Lazin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Laurence Dunmore\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Laurent Bouhnik\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Laurent Cantet\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Laurent Tirard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Laurie Collyer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lawrence Guterman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lawrence Kasanoff\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lawrence Kasdan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lee Daniels\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lee Tamahori\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lee Toland Krieger\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lee Unkrich\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Leigh Whannell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Len Wiseman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lena Dunham\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lenny Abrahamson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Leon Ford\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Leon Ichaso\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Leonard Farlinger\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Leonard Nimoy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Leos Carax\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Les Mayfield\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Leslie H. Martinson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Leslie Small\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Leslye Headland\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Levan Gabriadze\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lewis Gilbert\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lexi Alexander\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Li Zhang\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lijun Sun\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Liliana Cavani\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Linda Mendoza\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lionel C. Martin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lisa Azuelos\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lisa Cholodenko\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lisanne Pajot\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Liv Ullmann\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Livingston Oden\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Liz Friedlander\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lloyd Bacon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lloyd Kaufman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lluís Quílez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lone Scherfig\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lorene Scafaria\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lori Petty\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lori Silverbush\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Louis C.K.\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Louis Leterrier\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Louis Morneau\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lowell Sherman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Luc Besson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Luc Jacquet\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Luca Guadagnino\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lucile Hadzihalilovic\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lucio Fulci\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lucky McKee\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lucrecia Martel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Luis Llosa\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Luis Mandoki\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Luis Valdez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lukas Moodysson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Luke Dye\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Luke Greenfield\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lynn Shelton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Lynne Ramsay\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Léa Pool\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "M. Night Shyamalan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mabel Cheung\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mabrouk El Mechri\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Maggie Carey\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Maggie Greenwald\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Majid Majidi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Maksim Fadeev\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Malcolm D. Lee\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Malcolm Goodwin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mamoru Hosoda\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marc Abraham\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marc Bennett\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marc F. Adler\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marc Forby\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marc Forster\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marc Lawrence\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marc Levin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marc Schölermann\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marc Webb\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marcio Garcia\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marco Kreuzpaintner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marco Schnabel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marcos Siega\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marcus Dunstan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marcus Nispel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marcus Raboy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Maria Maggenti\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marianna Palka\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marielle Heller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mariette Monpierre\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marilyn Agrelo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mario Van Peebles\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Marius A. Markevicius\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark A.Z. Dippé\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Andrews\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Brown\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Christopher\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Dindal\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Griffiths\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Helfrich\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Herman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Illsley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark L. Lester\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Mylod\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Neveldine\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Osborne\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Pellington\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Piznarski\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Romanek\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Rosman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Rydell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Sandrich\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Steven Johnson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Tarlov\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Tonderai\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Waters\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mark Young\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mars Callahan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Martha Coolidge\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Martin Brest\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Martin Campbell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Martin Koolhoven\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Martin Lawrence\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Martin McDonagh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Martin Ritt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Martin Scorsese\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Martin Weisz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Martyn Pick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mary Harron\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mary Lambert\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mary McGuckian\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mary Pat Kelly\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Maryam Keshavarz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Masayuki Ochiai\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mateo Gil\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mathieu Amalric\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mathieu Kassovitz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matt Bettinelli-Olpin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matt Birch\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matt Cimber\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matt Dillon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matt Jackson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matt Johnson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matt Maiellaro\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matt Piedmont\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matt Reeves\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matt Walsh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matt Williams\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matthew Bright\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matthew Diamond\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matthew Hastings\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matthew O'Callaghan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matthew R. Anderson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matthew Robbins\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matthew Vaughn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matthew Watts\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Matty Rich\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Maurice Joyce\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Maurizio Benazzo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Max Färberböck\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Max Joseph\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Max Mayer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Maïwenn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "McG\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Meiert Avis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mel Brooks\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mel Gibson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mel Smith\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mel Stuart\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Melville Shavelson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Melvin Van Peebles\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mennan Yapo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Menno Meyjes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mervyn LeRoy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mic Rodgers\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Anderson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Apted\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Bay\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Burke\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Caton-Jones\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Chapman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Cimino\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Clancy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Cohn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Corrente\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Crichton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Cristofer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Cuesta\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Curtiz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael D. Sellers\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Dinner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Dougherty\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Dowse\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Gornick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Haneke\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Herz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Hoffman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Hoffman Jr.\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael J. Bassett\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Jai White\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Kang\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Landon Jr.\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Lehmann\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Lembeck\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Mann\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Martin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Mayer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael McCullers\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael McGowan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Meredith\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Moore\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael O. Sajbel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Patrick Jann\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Patrick King\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Polish\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Pressman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Radford\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Ritchie\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Roemer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Rymer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Schultz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Spierig\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Sucsy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Taliferro\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Tiddes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Tollin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Wadleigh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Walker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Winner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Winnick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michael Winterbottom\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michel Gondry\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michel Hazanavicius\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michel Leclerc\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Michel Orion Scott\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mick Jackson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mickey Liddell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Miguel Arteta\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Miguel Sapochnik\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mikael Håfström\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mikael Salomon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Barker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Bigelow\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Binder\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Bruce\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Cahill\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Disa\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Figgis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Flanagan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Gabriel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Hodges\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Judge\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Leigh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Marvin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Mayhall\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike McCoy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Mills\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Mitchell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Nawrocki\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Newell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike Nichols\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mike van Diem\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mikel Rueda\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Milos Forman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mimi Leder\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mira Nair\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Miranda July\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mitch Davis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mitchell Altieri\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mitchell Lichtenstein\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Molly Bernstein\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mona Fastvold\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Monte Hellman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mor Loushy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mora Stephens\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Morgan J. Freeman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Morgan Neville\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Morgan Spurlock\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Mort Nathan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Morten Tyldum\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Moustapha Akkad\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Myles Berkowitz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Måns Mårlind\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nacho Vigalondo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nadia Tass\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nadine Labaki\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nae Caranfil\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nancy Meyers\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nancy Walker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nanette Burstein\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nat Faxon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Natalie Bible'\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nate Parker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nathan Frankowski\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nathan Greno\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nathan Smith Jones\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Neal Brennan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Neema Barnette\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Neil Burger\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Neil Jordan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Neil LaBute\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Neil Marshall\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Neil Mcenery-West\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Neill Blomkamp\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Neill Dela Llana\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nelson McCormick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Newt Arnold\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Niall Johnson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nicholas Fackler\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nicholas Hytner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nicholas Jarecki\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nicholas Meyer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nicholas Ray\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nicholas Stoller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nicholaus Goossen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nick Cassavetes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nick Gomez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nick Hamm\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nick Hurran\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nick Love\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nick Murphy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nick Tomnay\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nickolas Perry\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nicolae Constantin Tanase\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nicolas Winding Refn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nicole Holofcener\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Niels Arden Oplev\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nigel Cole\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Niki Caro\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nils Gaup\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nima Nourizadeh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nimród Antal\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nnegest Likké\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Noah Baumbach\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Noah Buschel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Noam Murro\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Noel Marshall\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Nora Ephron\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Norman Ferguson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Norman Jewison\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ol Parker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Olatunde Osunsanmi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ole Bornedal\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ole Christian Madsen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Oleg Stepchenko\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Oliver Blackburn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Oliver Hirschbiegel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Oliver Parker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Oliver Stone\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Olivier Assayas\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Olivier Dahan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Olivier Megaton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Oren Moverman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Oren Peli\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Orson Welles\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ossie Davis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "P.J. Hogan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Pan Nalin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Panos Cosmatos\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paolo Monico\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paolo Sorrentino\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Pascal Arnold\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Pascal Chaumeil\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Pat Holden\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Pat O'Connor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Patrice Leconte\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Patricia Cardoso\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Patricia Riggen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Patricia Rozema\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Patrick Creadon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Patrick Gilles\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Patrick Gilmore\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Patrick Hughes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Patrick Lussier\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Patrick Meaney\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Patrick Read Johnson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Patrick Ryan Sims\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Patrick Stettner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Patrick Tatopoulos\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Patty Jenkins\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Abascal\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Andrew Williams\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Bartel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Bolger\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Bunnell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Crowder\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Donovan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Feig\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Fierlinger\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Fox\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Greengrass\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Gross\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Haggis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Hunter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul King\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Mazursky\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul McGuigan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Michael Glaser\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Schrader\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Thomas Anderson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Tibbitt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Verhoeven\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul W.S. Anderson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Weiland\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Paul Weitz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Pawel Pawlikowski\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Pece Dingo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Pedro Almodóvar\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Penelope Spheeris\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Penny Marshall\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Perry Andelin Blake\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Perry Lang\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Pete Docter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Pete Jones\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Pete Travis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Atencio\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Berg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Billingsley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Care\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Cattaneo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Chelsom\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Cousens\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter DeLuise\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Faiman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Farrelly\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Flinth\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter H. Hunt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Hastings\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Hedges\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Hewitt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Ho-Sun Chan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Howitt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Hyams\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Jackson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Kassovitz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Kosminsky\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Landesman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Lepeniotis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Lord\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter M. Cohen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter MacDonald\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Medak\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter R. Hunt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Ramsey\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Segal\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Sohn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Sollett\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Stebbings\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Webber\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Weir\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peter Yates\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Petter Næss\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Peyton Reed\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Phil Alden Robinson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Phil Claydon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Phil Joanou\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Phil Lord\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Phil Morrison\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Phil Traill\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Philip G. Atwell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Philip Kaufman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Philip Saville\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Philip Zlotorynski\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Phillip Noyce\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Phyllida Lloyd\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Pierre Coffin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Pierre Morel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Pitof\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Piyush Dinker Pandya\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Pou-Soi Cheang\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Prachya Pinkaew\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Preston A. Whitmore II\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Qasim Basir\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Quentin Dupieux\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Quentin Tarantino\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "R. Balki\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "R.J. Cutler\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RZA\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rachel Goldenberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rachel Perkins\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rachel Talalay\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rafa Lara\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Raja Gosnell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Raja Menon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rajkumar Hirani\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rakesh Roshan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rakeysh Omprakash Mehra\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ralph Fiennes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ralph Nelson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ralph Ziman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ramaa Mosley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rand Ravich\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Randal Kleiser\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Randall Miller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Randall Rubin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Randall Wallace\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Randy Moore\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rania Attieh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rawson Marshall Thurber\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ray Griggs\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ray Lawrence\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Raymond De Felitta\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rebecca Miller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Reed Cowan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Regardt van den Bergh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Reginald Hudlin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Reinhard Klooss\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Remo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Renny Harlin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "René Féret\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rian Johnson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ric Roman Waugh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rich Christiano\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rich Cowan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rich Moore\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Attenborough\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Ayoade\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Benjamin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Boddington\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Brooks\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Curtis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Donner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Dutcher\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard E. Grant\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Eyre\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Fleischer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Glatzer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard J. Lewis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Kelly\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Kwietniowski\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard LaGravenese\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Lester\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Linklater\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Loncraine\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Marquand\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Montoya\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Raymond\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Rich\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Schenkman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Shepard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Wallace\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Richard Williams\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rick Bieber\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rick Famuyiwa\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rick Friedberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rick Rosenthal\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rick de Oliveira\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ricki Stern\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ricky Gervais\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ridley Scott\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ringo Lam\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Risa Bramon Garcia\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rita Merson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ritesh Batra\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rob Bowman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rob Cohen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rob Hawk\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rob Hedden\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rob Letterman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rob Marshall\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rob McKittrick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rob Minkoff\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rob Pritts\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rob Reiner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rob Schmidt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rob Zombie\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robby Henson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Adetuyi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Altman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert B. Weide\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Ben Garant\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Bennett\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Butler\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert C. Cooper\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Cary\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert D. Webb\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Duvall\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Eggers\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Fontaine\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Greenwald\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Hall\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Harmon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Heath\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Iscove\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Kenner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Lee King\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Lorenz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Luketic\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert M. Young\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Marcarelli\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Moresco\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Mulligan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Redford\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Rodriguez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Rossen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Sarkies\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Schwentke\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Stevenson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Stromberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Towne\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Townsend\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Wise\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robert Zemeckis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robin Budd\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Robinson Devor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rod Lurie\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rodman Flender\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rodrigo Cortés\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rodrigo García\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Roger Allers\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Roger Avary\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Roger Christian\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Roger Donaldson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Roger Kumble\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Roger Michell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Roger Nygard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Roger Spottiswoode\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Roger Vadim\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rohan Sippy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rohit Jagessar\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rohit Jugraj\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Roland Emmerich\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Roland Joffé\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Roland Suso Richter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Roman Polanski\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Romesh Sharma\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ron Clements\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ron Fricke\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ron Howard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ron Maxwell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ron Shelton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ron Underwood\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ronald Neame\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ronan Chapalain\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ronny Yu\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rowan Joffe\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rowdy Herrington\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ruairi Robinson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ruba Nadda\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ruben Fleischer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ruggero Deodato\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rupert Sanders\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rupert Wainwright\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rupert Wyatt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Russ Meyer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Russell Crowe\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Russell Friedenberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Russell Holt\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Russell Mulcahy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Rusty Cundieff\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ryan Coogler\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ryan Fleck\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ryan Little\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ryan Murphy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ryan Smith\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ryûhei Kitamura\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "S.R. Bindler\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "S.S. Rajamouli\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sacha Bennett\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sadyk Sher-Niyaz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sai Varadan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sajid Khan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Salim Akil\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sally Potter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Salvador Carrasco\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sam Fell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sam Firstenberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sam Levinson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sam Martin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sam Mendes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sam Miller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sam Peckinpah\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sam Raimi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sam Taylor-Johnson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sam Weisman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sammo Kam-Bo Hung\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sanaa Hamri\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sanjay Rawal\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sara Newens\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sara Sugarman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sarah Gavron\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sarah Smith\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sarik Andreasyan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Saul Dibb\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scandar Copti\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scott Alexander\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scott Cooper\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scott Derrickson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scott Dow\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scott Foley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scott Frank\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scott Hicks\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scott Kalvert\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scott Mann\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scott Marshall\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scott Smith\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scott Speer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scott Stewart\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scott Walker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scott Waugh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Scott Ziehl\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sean Anders\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sean Byrne\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sean Durkin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sean McNamara\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sean Penn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Serdar Akar\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sergey Bodrov\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sergey Bondarchuk\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sergio Leone\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Seth Gordon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Seth MacFarlane\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Shana Feste\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Shane Acker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Shane Black\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Shane Carruth\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Shane Dawson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Shane Meadows\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Shari Springer Berman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sharon Greytak\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sharon Maguire\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sharron Miller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Shawn Levy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Shekar\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Shekhar Kapur\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sheldon Lettich\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sherman Alexie\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Shimit Amin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Shinji Aramaki\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Shintaro Shimosawa\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Shona Auerbach\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Shyam Madiraju\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Siddharth Anand\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Siddiq Barmak\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sidney J. Furie\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sidney Lumet\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Simeon Rice\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Simon Curtis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Simon Napier-Bell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Simon Wells\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Simon West\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Simon Wincer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Simon Yin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sngmoo Lee\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sofia Coppola\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sol Tryon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Spencer Susser\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Spike Jonze\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Spike Lee\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stacy Peralta\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stanley Donen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stanley Kramer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stanley Kubrick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stanley Tong\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stanton Barrett\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stefan C. Schaefer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stefan Ruzowitzky\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stefan Schwartz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stefen Fangmeier\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephan Elliott\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephen Carpenter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephen Chbosky\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephen Chow\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephen Daldry\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephen Frears\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephen Gaghan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephen Herek\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephen Hillenburg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephen Hopkins\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephen J. Anderson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephen Kay\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephen Kijak\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephen Langford\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephen Milburn Anderson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephen Norrington\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stephen Sommers\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sterling Van Wagenen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stevan Mena\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Antin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Barron\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Beck\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Bendelack\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Box\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Boyum\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Buscemi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Carr\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Carver\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Gomer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Hickner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve James\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Martino\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve McQueen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Miner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Oedekerk\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Pink\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Rash\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Taylor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steve Trenbirth\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steven Brill\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steven E. de Souza\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steven Quale\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steven R. Monroe\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steven Seagal\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steven Shainberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steven Soderbergh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steven Spielberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Steven Zaillian\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stewart Hendler\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stewart Raffill\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stig Bergqvist\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stiles White\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stuart Baird\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stuart Beattie\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stuart Gillard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stuart Gordon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stuart Hazeldine\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Stéphane Aubier\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sue Corcoran\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Susan Seidelman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Susan Stroman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Susanna White\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Susanne Bier\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sut Jhally\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sydney Pollack\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sylvain Chomet\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sylvain White\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sylvester Stallone\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Sylvio Tabet\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tadeo Garcia\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Taedong Park\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Takao Okawara\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Takashi Shimizu\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Takashi Yamazaki\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Takeshi Kitano\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tamara Jenkins\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tamra Davis\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tanner Beard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tara Subkoff\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tarsem Singh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tate Taylor\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tay Garnett\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Taylor Hackford\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ted Demme\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ted Kotcheff\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ted Post\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Teddy Chan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Terence Davies\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Terence Young\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Terrence Malick\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Terron R. Parsons\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Terry George\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Terry Gilliam\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Terry Zwigoff\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Thaddeus O'Sullivan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Thea Sharrock\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Theodore Melfi\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Theodore Witcher\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Thomas Bezucha\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Thomas Carter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Thomas L. Phillips\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Thomas Lilti\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Thomas Vinterberg\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Thor Freudenthal\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Thorbjørn Christoffersen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ti West\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tim Blake Nelson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tim Boxell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tim Burton\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tim Chambers\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tim Fywell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tim Heidecker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tim Hill\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tim Hunter\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tim Johnson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tim McCanlies\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tim Miller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tim Robbins\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tim Story\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Timothy Björklund\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Timothy Hines\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Timothy Woodward Jr.\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Timur Bekmambetov\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tina Gordon Chism\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tobe Hooper\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tod Williams\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Todd Field\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Todd Graff\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Todd Haynes\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Todd Lincoln\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Todd Phillips\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Todd Solondz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Todd Strauss-Schulson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Brady\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Dey\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom DiCillo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Elkins\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Ford\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Gormican\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Green\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Hanks\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Holland\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Hooper\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Kalin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom McCarthy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom McGrath\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom McLoughlin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Putnam\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Reeve\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Sanchez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Schulman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Seidman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Shadyac\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Tykwer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Vaughan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tom Walsh\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tomas Alfredson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tomm Moore\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tommy Lee Jones\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tommy Lee Wallace\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tommy O'Haver\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tommy Oliver\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tommy Wirkola\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tony Bancroft\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tony Bill\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tony Giglio\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tony Gilroy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tony Goldwyn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tony Jaa\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tony Kaye\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tony Krantz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tony Maylam\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tony Richardson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tony Scott\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tran Anh Hung\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Travis Cluff\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Travis Legge\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Travis Romero\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Travis Zariwny\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Trent Cooper\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Trey Parker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Troy Duffy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Troy Miller\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Troy Nixey\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tuck Tucker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tung-Shing Yee\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tyler Oliver\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Tyler Perry\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "U. Roberto Romano\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Udayan Prasad\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Uli Edel\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ulu Grosbard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Uwe Boll\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vadim Perelman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Valentine\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Valeri Milev\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vera Farmiga\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vic Armstrong\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vic Sarin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vicente Amorim\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vicky Jenson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vicky Jewson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Victor Fleming\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Victor Nunez\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Victor Salva\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vidhu Vinod Chopra\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vijay Chandar\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vincent Gallo\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vincent Paronnaud\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vincent Ward\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vincente Minnelli\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vincenzo Natali\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vipul Amrutlal Shah\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vivek Agnihotri\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vladlen Barbe\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Vondie Curtis-Hall\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "W.D. Hogan\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Wade Gasque\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Wajahat Rauf\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Wallace Wolodarsky\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Wally Pfister\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Walt Becker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Walter Hill\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Walter Lang\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Walter Murch\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Walter Salles\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Ward Roberts\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Warren Beatty\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Warren P. Sonoda\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Warren Sheppard\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Wayne Beach\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Wayne Kramer\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Wayne Thornley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Wayne Wang\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Werner Herzog\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Wes Anderson\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Wes Ball\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Wes Craven\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Whit Stillman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Wil Shriner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Will Canon\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Will Finn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Will Gluck\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Willard Huyck\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William A. Fraker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William A. Graham\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William Arntz\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William Bindley\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William Brent Bell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William Cottrell\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William Dear\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William Eubank\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William Friedkin\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William Gazecki\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William H. Macy\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William Kaufman\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William Malone\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William Phillips\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William Sachs\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William Shatner\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "William Wyler\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Wilson Yip\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Wolfgang Becker\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Wolfgang Petersen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Woo-Suk Kang\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Woody Allen\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Wych Kaosayananda\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Xavier Beauvois\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Xavier Gens\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Yarrow Cheney\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Yash Chopra\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Yimou Zhang\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Yorgos Lanthimos\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Youssef Delara\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Yuefeng Song\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Zach Braff\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Zach Cregger\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Zack Snyder\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Zack Ward\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Zackary Adler\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Zak Penn\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Zal Batmanglij\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Zoran Lisinac\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Álex de la Iglesia\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Émile Gaudreault\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Éric Tessier\n",
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Étienne Faure\n",
      "<class 'pandas.core.frame.DataFrame'>\n"
     ]
    }
   ],
   "source": [
    "for name,group in grouped:\n",
    "    print(name)\n",
    "    print(type(group))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 统计计算\n",
    "1. 单个统计量计算 mean/sum/std\n",
    "2. 多个统计量计算\n",
    "3. 不同列应用不同统计量\n",
    "\n",
    "<span class=\"mark\">分组计算很重要的一点是：**我们的每一个统计函数都是作用在每一个group上，不是单个样本，也不是全部数据**</span>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
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       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>duration</th>\n",
       "      <th>director_facebook_likes</th>\n",
       "      <th>actor_3_facebook_likes</th>\n",
       "      <th>actor_1_facebook_likes</th>\n",
       "      <th>gross</th>\n",
       "      <th>num_voted_users</th>\n",
       "      <th>cast_total_facebook_likes</th>\n",
       "      <th>facenumber_in_poster</th>\n",
       "      <th>num_user_for_reviews</th>\n",
       "      <th>budget</th>\n",
       "      <th>title_year</th>\n",
       "      <th>actor_2_facebook_likes</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>director_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A. Raven Cruz</th>\n",
       "      <td>3.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>639.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>534</td>\n",
       "      <td>1188</td>\n",
       "      <td>2.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>361.0</td>\n",
       "      <td>1.9</td>\n",
       "      <td>1.78</td>\n",
       "      <td>128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aaron Hann</th>\n",
       "      <td>29.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>13279</td>\n",
       "      <td>776</td>\n",
       "      <td>0.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aaron Schneider</th>\n",
       "      <td>160.0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>970.0</td>\n",
       "      <td>13000.0</td>\n",
       "      <td>9.176553e+06</td>\n",
       "      <td>19147</td>\n",
       "      <td>19330</td>\n",
       "      <td>1.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>7500000.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aaron Seltzer</th>\n",
       "      <td>99.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>64.0</td>\n",
       "      <td>729.0</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>4.854658e+07</td>\n",
       "      <td>50415</td>\n",
       "      <td>6539</td>\n",
       "      <td>0.0</td>\n",
       "      <td>613.0</td>\n",
       "      <td>20000000.0</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>869.0</td>\n",
       "      <td>2.7</td>\n",
       "      <td>1.85</td>\n",
       "      <td>806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Abel Ferrara</th>\n",
       "      <td>48.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>220.0</td>\n",
       "      <td>599.0</td>\n",
       "      <td>812.0</td>\n",
       "      <td>1.227324e+06</td>\n",
       "      <td>6921</td>\n",
       "      <td>3337</td>\n",
       "      <td>3.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>12500000.0</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>787.0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>1.85</td>\n",
       "      <td>344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Brooks</th>\n",
       "      <td>160.0</td>\n",
       "      <td>112.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>16000.0</td>\n",
       "      <td>3.197384e+07</td>\n",
       "      <td>127760</td>\n",
       "      <td>16289</td>\n",
       "      <td>5.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>7.2</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Carolla</th>\n",
       "      <td>14.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>563.0</td>\n",
       "      <td>1.059430e+05</td>\n",
       "      <td>1351</td>\n",
       "      <td>2628</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>1500000.0</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>485.0</td>\n",
       "      <td>6.1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Goldberg</th>\n",
       "      <td>22.0</td>\n",
       "      <td>111.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>2.580000e+03</td>\n",
       "      <td>1618</td>\n",
       "      <td>2564</td>\n",
       "      <td>2.0</td>\n",
       "      <td>40.0</td>\n",
       "      <td>1650000.0</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>163.0</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.35</td>\n",
       "      <td>63</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Green</th>\n",
       "      <td>229.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>134.0</td>\n",
       "      <td>488.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>23349</td>\n",
       "      <td>3668</td>\n",
       "      <td>0.0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>1500000.0</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>935.0</td>\n",
       "      <td>5.7</td>\n",
       "      <td>1.85</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Jay Epstein</th>\n",
       "      <td>14.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>227.0</td>\n",
       "      <td>387.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>9560</td>\n",
       "      <td>1190</td>\n",
       "      <td>6.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>295.0</td>\n",
       "      <td>3.8</td>\n",
       "      <td>1.85</td>\n",
       "      <td>636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Marcus</th>\n",
       "      <td>112.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>307.0</td>\n",
       "      <td>935.0</td>\n",
       "      <td>1.593507e+07</td>\n",
       "      <td>19331</td>\n",
       "      <td>2899</td>\n",
       "      <td>0.0</td>\n",
       "      <td>317.0</td>\n",
       "      <td>2500000.0</td>\n",
       "      <td>1993.0</td>\n",
       "      <td>805.0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>1.85</td>\n",
       "      <td>949</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam McKay</th>\n",
       "      <td>1481.0</td>\n",
       "      <td>715.0</td>\n",
       "      <td>1710.0</td>\n",
       "      <td>15968.0</td>\n",
       "      <td>712000.0</td>\n",
       "      <td>5.244497e+08</td>\n",
       "      <td>1115212</td>\n",
       "      <td>786121</td>\n",
       "      <td>20.0</td>\n",
       "      <td>2327.0</td>\n",
       "      <td>342000000.0</td>\n",
       "      <td>12056.0</td>\n",
       "      <td>51000.0</td>\n",
       "      <td>41.5</td>\n",
       "      <td>13.60</td>\n",
       "      <td>156000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Rapp</th>\n",
       "      <td>50.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>405.0</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>1.012280e+05</td>\n",
       "      <td>7228</td>\n",
       "      <td>20009</td>\n",
       "      <td>4.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>3500000.0</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>8000.0</td>\n",
       "      <td>6.4</td>\n",
       "      <td>1.85</td>\n",
       "      <td>414</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Rifkin</th>\n",
       "      <td>46.0</td>\n",
       "      <td>190.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>367.0</td>\n",
       "      <td>1471.0</td>\n",
       "      <td>4.193025e+06</td>\n",
       "      <td>30763</td>\n",
       "      <td>3223</td>\n",
       "      <td>0.0</td>\n",
       "      <td>195.0</td>\n",
       "      <td>15250000.0</td>\n",
       "      <td>4014.0</td>\n",
       "      <td>941.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>2.35</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Shankman</th>\n",
       "      <td>1234.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>1304.0</td>\n",
       "      <td>5265.0</td>\n",
       "      <td>50796.0</td>\n",
       "      <td>6.970719e+08</td>\n",
       "      <td>596135</td>\n",
       "      <td>74922</td>\n",
       "      <td>27.0</td>\n",
       "      <td>2653.0</td>\n",
       "      <td>425000000.0</td>\n",
       "      <td>16043.0</td>\n",
       "      <td>8181.0</td>\n",
       "      <td>47.7</td>\n",
       "      <td>18.80</td>\n",
       "      <td>53581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adrian Lyne</th>\n",
       "      <td>335.0</td>\n",
       "      <td>450.0</td>\n",
       "      <td>852.0</td>\n",
       "      <td>758.0</td>\n",
       "      <td>2516.0</td>\n",
       "      <td>3.110330e+08</td>\n",
       "      <td>182931</td>\n",
       "      <td>5724</td>\n",
       "      <td>0.0</td>\n",
       "      <td>980.0</td>\n",
       "      <td>85000000.0</td>\n",
       "      <td>7958.0</td>\n",
       "      <td>1110.0</td>\n",
       "      <td>25.6</td>\n",
       "      <td>7.40</td>\n",
       "      <td>3000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adrienne Shelly</th>\n",
       "      <td>173.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>336.0</td>\n",
       "      <td>597.0</td>\n",
       "      <td>1.906763e+07</td>\n",
       "      <td>37714</td>\n",
       "      <td>1981</td>\n",
       "      <td>1.0</td>\n",
       "      <td>204.0</td>\n",
       "      <td>2000000.0</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>541.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>1.85</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agnieszka Holland</th>\n",
       "      <td>78.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>238.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>3.527860e+05</td>\n",
       "      <td>11132</td>\n",
       "      <td>150</td>\n",
       "      <td>0.0</td>\n",
       "      <td>86.0</td>\n",
       "      <td>11000000.0</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agnieszka Wojtowicz-Vosloo</th>\n",
       "      <td>138.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>329.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>1.082290e+05</td>\n",
       "      <td>30836</td>\n",
       "      <td>15860</td>\n",
       "      <td>1.0</td>\n",
       "      <td>137.0</td>\n",
       "      <td>4500000.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>5.9</td>\n",
       "      <td>2.35</td>\n",
       "      <td>7000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agustín Díaz Yanes</th>\n",
       "      <td>31.0</td>\n",
       "      <td>145.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>278.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>10266</td>\n",
       "      <td>11669</td>\n",
       "      <td>1.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>24000000.0</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>6.1</td>\n",
       "      <td>1.85</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aki Kaurismäki</th>\n",
       "      <td>205.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>592.0</td>\n",
       "      <td>36.0</td>\n",
       "      <td>232.0</td>\n",
       "      <td>6.117090e+05</td>\n",
       "      <td>15267</td>\n",
       "      <td>391</td>\n",
       "      <td>1.0</td>\n",
       "      <td>41.0</td>\n",
       "      <td>3850000.0</td>\n",
       "      <td>2011.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>7.2</td>\n",
       "      <td>1.85</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Akira Kurosawa</th>\n",
       "      <td>178.0</td>\n",
       "      <td>336.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>319.0</td>\n",
       "      <td>3.179170e+05</td>\n",
       "      <td>232478</td>\n",
       "      <td>368</td>\n",
       "      <td>6.0</td>\n",
       "      <td>636.0</td>\n",
       "      <td>13900000.0</td>\n",
       "      <td>3947.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>16.2</td>\n",
       "      <td>3.22</td>\n",
       "      <td>11355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Akiva Goldsman</th>\n",
       "      <td>189.0</td>\n",
       "      <td>118.0</td>\n",
       "      <td>167.0</td>\n",
       "      <td>778.0</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>2.245100e+04</td>\n",
       "      <td>41288</td>\n",
       "      <td>22447</td>\n",
       "      <td>0.0</td>\n",
       "      <td>126.0</td>\n",
       "      <td>60000000.0</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>882.0</td>\n",
       "      <td>6.2</td>\n",
       "      <td>2.35</td>\n",
       "      <td>17000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Akiva Schaffer</th>\n",
       "      <td>641.0</td>\n",
       "      <td>292.0</td>\n",
       "      <td>246.0</td>\n",
       "      <td>1505.0</td>\n",
       "      <td>2118.0</td>\n",
       "      <td>8.262185e+07</td>\n",
       "      <td>268038</td>\n",
       "      <td>7036</td>\n",
       "      <td>13.0</td>\n",
       "      <td>563.0</td>\n",
       "      <td>136000000.0</td>\n",
       "      <td>6031.0</td>\n",
       "      <td>1616.0</td>\n",
       "      <td>18.1</td>\n",
       "      <td>7.05</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Al Franklin</th>\n",
       "      <td>0.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>471.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>24</td>\n",
       "      <td>1399</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>300000.0</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>320.0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>16.00</td>\n",
       "      <td>85</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Al Silliman Jr.</th>\n",
       "      <td>21.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>161</td>\n",
       "      <td>24</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>100000.0</td>\n",
       "      <td>1969.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>1.37</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alain Resnais</th>\n",
       "      <td>129.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>752.0</td>\n",
       "      <td>59.0</td>\n",
       "      <td>412.0</td>\n",
       "      <td>4.036490e+05</td>\n",
       "      <td>3174</td>\n",
       "      <td>799</td>\n",
       "      <td>0.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>2.35</td>\n",
       "      <td>512</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alan Alda</th>\n",
       "      <td>6.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>146.0</td>\n",
       "      <td>804.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3157</td>\n",
       "      <td>1285</td>\n",
       "      <td>2.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1981.0</td>\n",
       "      <td>167.0</td>\n",
       "      <td>7.2</td>\n",
       "      <td>1.85</td>\n",
       "      <td>337</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alan Cohn</th>\n",
       "      <td>37.0</td>\n",
       "      <td>96.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>654.0</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>1.506290e+07</td>\n",
       "      <td>11729</td>\n",
       "      <td>6861</td>\n",
       "      <td>0.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>14000000.0</td>\n",
       "      <td>1998.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>1.85</td>\n",
       "      <td>645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alan J. Pakula</th>\n",
       "      <td>109.0</td>\n",
       "      <td>252.0</td>\n",
       "      <td>158.0</td>\n",
       "      <td>2956.0</td>\n",
       "      <td>29000.0</td>\n",
       "      <td>1.436452e+08</td>\n",
       "      <td>105171</td>\n",
       "      <td>56151</td>\n",
       "      <td>0.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>131000000.0</td>\n",
       "      <td>3990.0</td>\n",
       "      <td>19000.0</td>\n",
       "      <td>12.6</td>\n",
       "      <td>4.70</td>\n",
       "      <td>979</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Phillips</th>\n",
       "      <td>15.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>499.0</td>\n",
       "      <td>764.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3015</td>\n",
       "      <td>2876</td>\n",
       "      <td>1.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>10000000.0</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>716.0</td>\n",
       "      <td>6.5</td>\n",
       "      <td>2.35</td>\n",
       "      <td>850</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Sachs</th>\n",
       "      <td>24.0</td>\n",
       "      <td>95.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>60.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1955</td>\n",
       "      <td>396</td>\n",
       "      <td>0.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1980.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>3.4</td>\n",
       "      <td>2.35</td>\n",
       "      <td>438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Shatner</th>\n",
       "      <td>98.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>643.0</td>\n",
       "      <td>12000.0</td>\n",
       "      <td>5.521005e+07</td>\n",
       "      <td>43743</td>\n",
       "      <td>14710</td>\n",
       "      <td>1.0</td>\n",
       "      <td>293.0</td>\n",
       "      <td>27800000.0</td>\n",
       "      <td>1989.0</td>\n",
       "      <td>664.0</td>\n",
       "      <td>5.4</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Wyler</th>\n",
       "      <td>97.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>355.0</td>\n",
       "      <td>188.0</td>\n",
       "      <td>749.0</td>\n",
       "      <td>2.365000e+07</td>\n",
       "      <td>40359</td>\n",
       "      <td>1941</td>\n",
       "      <td>5.0</td>\n",
       "      <td>235.0</td>\n",
       "      <td>2100000.0</td>\n",
       "      <td>1946.0</td>\n",
       "      <td>208.0</td>\n",
       "      <td>8.1</td>\n",
       "      <td>1.37</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson Yip</th>\n",
       "      <td>78.0</td>\n",
       "      <td>105.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>461.0</td>\n",
       "      <td>2.126511e+06</td>\n",
       "      <td>21912</td>\n",
       "      <td>615</td>\n",
       "      <td>0.0</td>\n",
       "      <td>45.0</td>\n",
       "      <td>36000000.0</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>79.0</td>\n",
       "      <td>7.2</td>\n",
       "      <td>2.35</td>\n",
       "      <td>12000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wolfgang Becker</th>\n",
       "      <td>153.0</td>\n",
       "      <td>121.0</td>\n",
       "      <td>31.0</td>\n",
       "      <td>43.0</td>\n",
       "      <td>65.0</td>\n",
       "      <td>4.063859e+06</td>\n",
       "      <td>114407</td>\n",
       "      <td>200</td>\n",
       "      <td>2.0</td>\n",
       "      <td>225.0</td>\n",
       "      <td>4800000.0</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>51.0</td>\n",
       "      <td>7.7</td>\n",
       "      <td>1.85</td>\n",
       "      <td>11000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wolfgang Petersen</th>\n",
       "      <td>1083.0</td>\n",
       "      <td>1062.0</td>\n",
       "      <td>1743.0</td>\n",
       "      <td>4040.0</td>\n",
       "      <td>128669.0</td>\n",
       "      <td>6.283797e+08</td>\n",
       "      <td>1102198</td>\n",
       "      <td>169099</td>\n",
       "      <td>7.0</td>\n",
       "      <td>4335.0</td>\n",
       "      <td>651000000.0</td>\n",
       "      <td>13967.0</td>\n",
       "      <td>28971.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>15.45</td>\n",
       "      <td>32000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Woo-Suk Kang</th>\n",
       "      <td>15.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>3290</td>\n",
       "      <td>97</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>8000000.0</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>7.2</td>\n",
       "      <td>2.35</td>\n",
       "      <td>387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Woody Allen</th>\n",
       "      <td>3599.0</td>\n",
       "      <td>2194.0</td>\n",
       "      <td>242000.0</td>\n",
       "      <td>8562.0</td>\n",
       "      <td>184847.0</td>\n",
       "      <td>3.083454e+08</td>\n",
       "      <td>1593777</td>\n",
       "      <td>230398</td>\n",
       "      <td>22.0</td>\n",
       "      <td>4820.0</td>\n",
       "      <td>314500000.0</td>\n",
       "      <td>43934.0</td>\n",
       "      <td>27437.0</td>\n",
       "      <td>154.2</td>\n",
       "      <td>40.07</td>\n",
       "      <td>161735</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wych Kaosayananda</th>\n",
       "      <td>92.0</td>\n",
       "      <td>91.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>298.0</td>\n",
       "      <td>349.0</td>\n",
       "      <td>1.429484e+07</td>\n",
       "      <td>16761</td>\n",
       "      <td>1846</td>\n",
       "      <td>1.0</td>\n",
       "      <td>277.0</td>\n",
       "      <td>70000000.0</td>\n",
       "      <td>2002.0</td>\n",
       "      <td>324.0</td>\n",
       "      <td>3.6</td>\n",
       "      <td>2.35</td>\n",
       "      <td>391</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Xavier Beauvois</th>\n",
       "      <td>195.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>3.950029e+06</td>\n",
       "      <td>12411</td>\n",
       "      <td>416</td>\n",
       "      <td>0.0</td>\n",
       "      <td>89.0</td>\n",
       "      <td>4000000.0</td>\n",
       "      <td>2010.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>7.2</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Xavier Gens</th>\n",
       "      <td>367.0</td>\n",
       "      <td>216.0</td>\n",
       "      <td>174.0</td>\n",
       "      <td>885.0</td>\n",
       "      <td>2866.0</td>\n",
       "      <td>3.970953e+07</td>\n",
       "      <td>171291</td>\n",
       "      <td>7044</td>\n",
       "      <td>5.0</td>\n",
       "      <td>602.0</td>\n",
       "      <td>27000000.0</td>\n",
       "      <td>4018.0</td>\n",
       "      <td>1477.0</td>\n",
       "      <td>12.1</td>\n",
       "      <td>4.70</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yarrow Cheney</th>\n",
       "      <td>165.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>745.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>3.235055e+08</td>\n",
       "      <td>24407</td>\n",
       "      <td>4782</td>\n",
       "      <td>0.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>75000000.0</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>904.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>1.85</td>\n",
       "      <td>36000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yash Chopra</th>\n",
       "      <td>79.0</td>\n",
       "      <td>368.0</td>\n",
       "      <td>294.0</td>\n",
       "      <td>1397.0</td>\n",
       "      <td>16000.0</td>\n",
       "      <td>5.969277e+06</td>\n",
       "      <td>76745</td>\n",
       "      <td>23746</td>\n",
       "      <td>4.0</td>\n",
       "      <td>405.0</td>\n",
       "      <td>14217600.0</td>\n",
       "      <td>4016.0</td>\n",
       "      <td>3860.0</td>\n",
       "      <td>14.8</td>\n",
       "      <td>4.70</td>\n",
       "      <td>14000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yimou Zhang</th>\n",
       "      <td>1426.0</td>\n",
       "      <td>838.0</td>\n",
       "      <td>4888.0</td>\n",
       "      <td>1204.0</td>\n",
       "      <td>35530.0</td>\n",
       "      <td>1.854461e+07</td>\n",
       "      <td>473877</td>\n",
       "      <td>38827</td>\n",
       "      <td>18.0</td>\n",
       "      <td>2521.0</td>\n",
       "      <td>301000000.0</td>\n",
       "      <td>16057.0</td>\n",
       "      <td>2035.0</td>\n",
       "      <td>56.7</td>\n",
       "      <td>18.80</td>\n",
       "      <td>14568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yorgos Lanthimos</th>\n",
       "      <td>211.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>252.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>1.101970e+05</td>\n",
       "      <td>44864</td>\n",
       "      <td>126</td>\n",
       "      <td>0.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>7.3</td>\n",
       "      <td>2.35</td>\n",
       "      <td>13000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Youssef Delara</th>\n",
       "      <td>33.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>654.0</td>\n",
       "      <td>4000.0</td>\n",
       "      <td>2.833383e+06</td>\n",
       "      <td>1614</td>\n",
       "      <td>6928</td>\n",
       "      <td>1.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>1227000.0</td>\n",
       "      <td>4025.0</td>\n",
       "      <td>960.0</td>\n",
       "      <td>10.9</td>\n",
       "      <td>4.70</td>\n",
       "      <td>406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yuefeng Song</th>\n",
       "      <td>4.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>2169</td>\n",
       "      <td>196</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.0</td>\n",
       "      <td>40000000.0</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>6.4</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zach Braff</th>\n",
       "      <td>354.0</td>\n",
       "      <td>208.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>673.0</td>\n",
       "      <td>17625.0</td>\n",
       "      <td>3.037016e+07</td>\n",
       "      <td>216936</td>\n",
       "      <td>20602</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1071.0</td>\n",
       "      <td>8500000.0</td>\n",
       "      <td>4018.0</td>\n",
       "      <td>1379.0</td>\n",
       "      <td>14.3</td>\n",
       "      <td>4.70</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zach Cregger</th>\n",
       "      <td>76.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>263.0</td>\n",
       "      <td>373.0</td>\n",
       "      <td>4.542775e+06</td>\n",
       "      <td>18313</td>\n",
       "      <td>1831</td>\n",
       "      <td>2.0</td>\n",
       "      <td>73.0</td>\n",
       "      <td>6000000.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>308.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>1.85</td>\n",
       "      <td>985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zack Snyder</th>\n",
       "      <td>3514.0</td>\n",
       "      <td>1107.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7011.0</td>\n",
       "      <td>60986.0</td>\n",
       "      <td>1.149193e+09</td>\n",
       "      <td>2572138</td>\n",
       "      <td>112064</td>\n",
       "      <td>6.0</td>\n",
       "      <td>12048.0</td>\n",
       "      <td>884000000.0</td>\n",
       "      <td>16073.0</td>\n",
       "      <td>27398.0</td>\n",
       "      <td>57.4</td>\n",
       "      <td>18.80</td>\n",
       "      <td>418000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zack Ward</th>\n",
       "      <td>15.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>662.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>662.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>436</td>\n",
       "      <td>1498</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2016.0</td>\n",
       "      <td>290.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>378</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zackary Adler</th>\n",
       "      <td>10.0</td>\n",
       "      <td>110.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>109.0</td>\n",
       "      <td>490.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1510</td>\n",
       "      <td>881</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26.0</td>\n",
       "      <td>2500000.0</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>159.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zak Penn</th>\n",
       "      <td>60.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>3.683000e+04</td>\n",
       "      <td>3291</td>\n",
       "      <td>256</td>\n",
       "      <td>0.0</td>\n",
       "      <td>63.0</td>\n",
       "      <td>1400000.0</td>\n",
       "      <td>2004.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>1.85</td>\n",
       "      <td>400</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zal Batmanglij</th>\n",
       "      <td>336.0</td>\n",
       "      <td>201.0</td>\n",
       "      <td>258.0</td>\n",
       "      <td>882.0</td>\n",
       "      <td>10120.0</td>\n",
       "      <td>2.673910e+06</td>\n",
       "      <td>57631</td>\n",
       "      <td>13691</td>\n",
       "      <td>4.0</td>\n",
       "      <td>188.0</td>\n",
       "      <td>6500000.0</td>\n",
       "      <td>4024.0</td>\n",
       "      <td>1037.0</td>\n",
       "      <td>13.6</td>\n",
       "      <td>4.20</td>\n",
       "      <td>12000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoran Lisinac</th>\n",
       "      <td>17.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>431.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>330</td>\n",
       "      <td>1087</td>\n",
       "      <td>3.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>250000.0</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>297.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>1.85</td>\n",
       "      <td>231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Álex de la Iglesia</th>\n",
       "      <td>71.0</td>\n",
       "      <td>104.0</td>\n",
       "      <td>275.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>439.0</td>\n",
       "      <td>3.607000e+03</td>\n",
       "      <td>22753</td>\n",
       "      <td>940</td>\n",
       "      <td>4.0</td>\n",
       "      <td>94.0</td>\n",
       "      <td>10000000.0</td>\n",
       "      <td>2008.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>6.1</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Émile Gaudreault</th>\n",
       "      <td>67.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>636.0</td>\n",
       "      <td>6.239558e+06</td>\n",
       "      <td>5548</td>\n",
       "      <td>1033</td>\n",
       "      <td>0.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>5000000.0</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>210.0</td>\n",
       "      <td>6.7</td>\n",
       "      <td>1.85</td>\n",
       "      <td>352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Éric Tessier</th>\n",
       "      <td>9.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>1003</td>\n",
       "      <td>79</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>3200000.0</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>1.85</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Étienne Faure</th>\n",
       "      <td>9.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>569</td>\n",
       "      <td>19</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>500000.0</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.3</td>\n",
       "      <td>1.78</td>\n",
       "      <td>114</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2398 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                            num_critic_for_reviews  duration  \\\n",
       "director_name                                                  \n",
       "A. Raven Cruz                                  3.0      97.0   \n",
       "Aaron Hann                                    29.0      87.0   \n",
       "Aaron Schneider                              160.0     100.0   \n",
       "Aaron Seltzer                                 99.0      85.0   \n",
       "Abel Ferrara                                  48.0      99.0   \n",
       "Adam Brooks                                  160.0     112.0   \n",
       "Adam Carolla                                  14.0      98.0   \n",
       "Adam Goldberg                                 22.0     111.0   \n",
       "Adam Green                                   229.0      93.0   \n",
       "Adam Jay Epstein                              14.0      76.0   \n",
       "Adam Marcus                                  112.0      91.0   \n",
       "Adam McKay                                  1481.0     715.0   \n",
       "Adam Rapp                                     50.0      98.0   \n",
       "Adam Rifkin                                   46.0     190.0   \n",
       "Adam Shankman                               1234.0     850.0   \n",
       "Adrian Lyne                                  335.0     450.0   \n",
       "Adrienne Shelly                              173.0     108.0   \n",
       "Agnieszka Holland                             78.0     104.0   \n",
       "Agnieszka Wojtowicz-Vosloo                   138.0     104.0   \n",
       "Agustín Díaz Yanes                            31.0     145.0   \n",
       "Aki Kaurismäki                               205.0      93.0   \n",
       "Akira Kurosawa                               178.0     336.0   \n",
       "Akiva Goldsman                               189.0     118.0   \n",
       "Akiva Schaffer                               641.0     292.0   \n",
       "Al Franklin                                    0.0      96.0   \n",
       "Al Silliman Jr.                               21.0      93.0   \n",
       "Alain Resnais                                129.0     104.0   \n",
       "Alan Alda                                      6.0     107.0   \n",
       "Alan Cohn                                     37.0      96.0   \n",
       "Alan J. Pakula                               109.0     252.0   \n",
       "...                                            ...       ...   \n",
       "William Phillips                              15.0      89.0   \n",
       "William Sachs                                 24.0      95.0   \n",
       "William Shatner                               98.0     107.0   \n",
       "William Wyler                                 97.0     172.0   \n",
       "Wilson Yip                                    78.0     105.0   \n",
       "Wolfgang Becker                              153.0     121.0   \n",
       "Wolfgang Petersen                           1083.0    1062.0   \n",
       "Woo-Suk Kang                                  15.0     135.0   \n",
       "Woody Allen                                 3599.0    2194.0   \n",
       "Wych Kaosayananda                             92.0      91.0   \n",
       "Xavier Beauvois                              195.0     122.0   \n",
       "Xavier Gens                                  367.0     216.0   \n",
       "Yarrow Cheney                                165.0      87.0   \n",
       "Yash Chopra                                   79.0     368.0   \n",
       "Yimou Zhang                                 1426.0     838.0   \n",
       "Yorgos Lanthimos                             211.0      94.0   \n",
       "Youssef Delara                                33.0     168.0   \n",
       "Yuefeng Song                                   4.0      88.0   \n",
       "Zach Braff                                   354.0     208.0   \n",
       "Zach Cregger                                  76.0      90.0   \n",
       "Zack Snyder                                 3514.0    1107.0   \n",
       "Zack Ward                                     15.0      92.0   \n",
       "Zackary Adler                                 10.0     110.0   \n",
       "Zak Penn                                      60.0      94.0   \n",
       "Zal Batmanglij                               336.0     201.0   \n",
       "Zoran Lisinac                                 17.0     108.0   \n",
       "Álex de la Iglesia                            71.0     104.0   \n",
       "Émile Gaudreault                              67.0      92.0   \n",
       "Éric Tessier                                   9.0      99.0   \n",
       "Étienne Faure                                  9.0      98.0   \n",
       "\n",
       "                            director_facebook_likes  actor_3_facebook_likes  \\\n",
       "director_name                                                                 \n",
       "A. Raven Cruz                                   0.0                    94.0   \n",
       "Aaron Hann                                      0.0                    94.0   \n",
       "Aaron Schneider                                11.0                   970.0   \n",
       "Aaron Seltzer                                  64.0                   729.0   \n",
       "Abel Ferrara                                  220.0                   599.0   \n",
       "Adam Brooks                                    20.0                    61.0   \n",
       "Adam Carolla                                  102.0                   360.0   \n",
       "Adam Goldberg                                1000.0                   127.0   \n",
       "Adam Green                                    134.0                   488.0   \n",
       "Adam Jay Epstein                                0.0                   227.0   \n",
       "Adam Marcus                                    18.0                   307.0   \n",
       "Adam McKay                                   1710.0                 15968.0   \n",
       "Adam Rapp                                       9.0                   405.0   \n",
       "Adam Rifkin                                   178.0                   367.0   \n",
       "Adam Shankman                                1304.0                  5265.0   \n",
       "Adrian Lyne                                   852.0                   758.0   \n",
       "Adrienne Shelly                               191.0                   336.0   \n",
       "Agnieszka Holland                             238.0                    22.0   \n",
       "Agnieszka Wojtowicz-Vosloo                      0.0                   329.0   \n",
       "Agustín Díaz Yanes                             13.0                   278.0   \n",
       "Aki Kaurismäki                                592.0                    36.0   \n",
       "Akira Kurosawa                                  0.0                     8.0   \n",
       "Akiva Goldsman                                167.0                   778.0   \n",
       "Akiva Schaffer                                246.0                  1505.0   \n",
       "Al Franklin                                     0.0                   270.0   \n",
       "Al Silliman Jr.                                 0.0                     0.0   \n",
       "Alain Resnais                                 752.0                    59.0   \n",
       "Alan Alda                                       0.0                   146.0   \n",
       "Alan Cohn                                       0.0                   654.0   \n",
       "Alan J. Pakula                                158.0                  2956.0   \n",
       "...                                             ...                     ...   \n",
       "William Phillips                                3.0                   499.0   \n",
       "William Sachs                                  14.0                    60.0   \n",
       "William Shatner                                 0.0                   643.0   \n",
       "William Wyler                                 355.0                   188.0   \n",
       "Wilson Yip                                     25.0                    51.0   \n",
       "Wolfgang Becker                                31.0                    43.0   \n",
       "Wolfgang Petersen                            1743.0                  4040.0   \n",
       "Woo-Suk Kang                                    0.0                    13.0   \n",
       "Woody Allen                                242000.0                  8562.0   \n",
       "Wych Kaosayananda                               8.0                   298.0   \n",
       "Xavier Beauvois                                22.0                    32.0   \n",
       "Xavier Gens                                   174.0                   885.0   \n",
       "Yarrow Cheney                                  11.0                   745.0   \n",
       "Yash Chopra                                   294.0                  1397.0   \n",
       "Yimou Zhang                                  4888.0                  1204.0   \n",
       "Yorgos Lanthimos                              252.0                    14.0   \n",
       "Youssef Delara                                 16.0                   654.0   \n",
       "Yuefeng Song                                    0.0                    46.0   \n",
       "Zach Braff                                      0.0                   673.0   \n",
       "Zach Cregger                                  138.0                   263.0   \n",
       "Zack Snyder                                     0.0                  7011.0   \n",
       "Zack Ward                                     662.0                   161.0   \n",
       "Zackary Adler                                   0.0                   109.0   \n",
       "Zak Penn                                       87.0                    37.0   \n",
       "Zal Batmanglij                                258.0                   882.0   \n",
       "Zoran Lisinac                                   0.0                   142.0   \n",
       "Álex de la Iglesia                            275.0                   102.0   \n",
       "Émile Gaudreault                                9.0                    71.0   \n",
       "Éric Tessier                                    0.0                     6.0   \n",
       "Étienne Faure                                  77.0                     0.0   \n",
       "\n",
       "                            actor_1_facebook_likes         gross  \\\n",
       "director_name                                                      \n",
       "A. Raven Cruz                                639.0  0.000000e+00   \n",
       "Aaron Hann                                   160.0  0.000000e+00   \n",
       "Aaron Schneider                            13000.0  9.176553e+06   \n",
       "Aaron Seltzer                               3000.0  4.854658e+07   \n",
       "Abel Ferrara                                 812.0  1.227324e+06   \n",
       "Adam Brooks                                16000.0  3.197384e+07   \n",
       "Adam Carolla                                 563.0  1.059430e+05   \n",
       "Adam Goldberg                               2000.0  2.580000e+03   \n",
       "Adam Green                                   936.0  0.000000e+00   \n",
       "Adam Jay Epstein                             387.0  0.000000e+00   \n",
       "Adam Marcus                                  935.0  1.593507e+07   \n",
       "Adam McKay                                712000.0  5.244497e+08   \n",
       "Adam Rapp                                  11000.0  1.012280e+05   \n",
       "Adam Rifkin                                 1471.0  4.193025e+06   \n",
       "Adam Shankman                              50796.0  6.970719e+08   \n",
       "Adrian Lyne                                 2516.0  3.110330e+08   \n",
       "Adrienne Shelly                              597.0  1.906763e+07   \n",
       "Agnieszka Holland                             60.0  3.527860e+05   \n",
       "Agnieszka Wojtowicz-Vosloo                 14000.0  1.082290e+05   \n",
       "Agustín Díaz Yanes                         10000.0  0.000000e+00   \n",
       "Aki Kaurismäki                               232.0  6.117090e+05   \n",
       "Akira Kurosawa                               319.0  3.179170e+05   \n",
       "Akiva Goldsman                             20000.0  2.245100e+04   \n",
       "Akiva Schaffer                              2118.0  8.262185e+07   \n",
       "Al Franklin                                  471.0  0.000000e+00   \n",
       "Al Silliman Jr.                               12.0  0.000000e+00   \n",
       "Alain Resnais                                412.0  4.036490e+05   \n",
       "Alan Alda                                    804.0  0.000000e+00   \n",
       "Alan Cohn                                   3000.0  1.506290e+07   \n",
       "Alan J. Pakula                             29000.0  1.436452e+08   \n",
       "...                                            ...           ...   \n",
       "William Phillips                             764.0  0.000000e+00   \n",
       "William Sachs                                113.0  0.000000e+00   \n",
       "William Shatner                            12000.0  5.521005e+07   \n",
       "William Wyler                                749.0  2.365000e+07   \n",
       "Wilson Yip                                   461.0  2.126511e+06   \n",
       "Wolfgang Becker                               65.0  4.063859e+06   \n",
       "Wolfgang Petersen                         128669.0  6.283797e+08   \n",
       "Woo-Suk Kang                                  28.0  0.000000e+00   \n",
       "Woody Allen                               184847.0  3.083454e+08   \n",
       "Wych Kaosayananda                            349.0  1.429484e+07   \n",
       "Xavier Beauvois                              186.0  3.950029e+06   \n",
       "Xavier Gens                                 2866.0  3.970953e+07   \n",
       "Yarrow Cheney                               1000.0  3.235055e+08   \n",
       "Yash Chopra                                16000.0  5.969277e+06   \n",
       "Yimou Zhang                                35530.0  1.854461e+07   \n",
       "Yorgos Lanthimos                              47.0  1.101970e+05   \n",
       "Youssef Delara                              4000.0  2.833383e+06   \n",
       "Yuefeng Song                                  76.0  0.000000e+00   \n",
       "Zach Braff                                 17625.0  3.037016e+07   \n",
       "Zach Cregger                                 373.0  4.542775e+06   \n",
       "Zack Snyder                                60986.0  1.149193e+09   \n",
       "Zack Ward                                    662.0  0.000000e+00   \n",
       "Zackary Adler                                490.0  0.000000e+00   \n",
       "Zak Penn                                      87.0  3.683000e+04   \n",
       "Zal Batmanglij                             10120.0  2.673910e+06   \n",
       "Zoran Lisinac                                431.0  0.000000e+00   \n",
       "Álex de la Iglesia                           439.0  3.607000e+03   \n",
       "Émile Gaudreault                             636.0  6.239558e+06   \n",
       "Éric Tessier                                  50.0  0.000000e+00   \n",
       "Étienne Faure                                 19.0  0.000000e+00   \n",
       "\n",
       "                            num_voted_users  cast_total_facebook_likes  \\\n",
       "director_name                                                            \n",
       "A. Raven Cruz                           534                       1188   \n",
       "Aaron Hann                            13279                        776   \n",
       "Aaron Schneider                       19147                      19330   \n",
       "Aaron Seltzer                         50415                       6539   \n",
       "Abel Ferrara                           6921                       3337   \n",
       "Adam Brooks                          127760                      16289   \n",
       "Adam Carolla                           1351                       2628   \n",
       "Adam Goldberg                          1618                       2564   \n",
       "Adam Green                            23349                       3668   \n",
       "Adam Jay Epstein                       9560                       1190   \n",
       "Adam Marcus                           19331                       2899   \n",
       "Adam McKay                          1115212                     786121   \n",
       "Adam Rapp                              7228                      20009   \n",
       "Adam Rifkin                           30763                       3223   \n",
       "Adam Shankman                        596135                      74922   \n",
       "Adrian Lyne                          182931                       5724   \n",
       "Adrienne Shelly                       37714                       1981   \n",
       "Agnieszka Holland                     11132                        150   \n",
       "Agnieszka Wojtowicz-Vosloo            30836                      15860   \n",
       "Agustín Díaz Yanes                    10266                      11669   \n",
       "Aki Kaurismäki                        15267                        391   \n",
       "Akira Kurosawa                       232478                        368   \n",
       "Akiva Goldsman                        41288                      22447   \n",
       "Akiva Schaffer                       268038                       7036   \n",
       "Al Franklin                              24                       1399   \n",
       "Al Silliman Jr.                         161                         24   \n",
       "Alain Resnais                          3174                        799   \n",
       "Alan Alda                              3157                       1285   \n",
       "Alan Cohn                             11729                       6861   \n",
       "Alan J. Pakula                       105171                      56151   \n",
       "...                                     ...                        ...   \n",
       "William Phillips                       3015                       2876   \n",
       "William Sachs                          1955                        396   \n",
       "William Shatner                       43743                      14710   \n",
       "William Wyler                         40359                       1941   \n",
       "Wilson Yip                            21912                        615   \n",
       "Wolfgang Becker                      114407                        200   \n",
       "Wolfgang Petersen                   1102198                     169099   \n",
       "Woo-Suk Kang                           3290                         97   \n",
       "Woody Allen                         1593777                     230398   \n",
       "Wych Kaosayananda                     16761                       1846   \n",
       "Xavier Beauvois                       12411                        416   \n",
       "Xavier Gens                          171291                       7044   \n",
       "Yarrow Cheney                         24407                       4782   \n",
       "Yash Chopra                           76745                      23746   \n",
       "Yimou Zhang                          473877                      38827   \n",
       "Yorgos Lanthimos                      44864                        126   \n",
       "Youssef Delara                         1614                       6928   \n",
       "Yuefeng Song                           2169                        196   \n",
       "Zach Braff                           216936                      20602   \n",
       "Zach Cregger                          18313                       1831   \n",
       "Zack Snyder                         2572138                     112064   \n",
       "Zack Ward                               436                       1498   \n",
       "Zackary Adler                          1510                        881   \n",
       "Zak Penn                               3291                        256   \n",
       "Zal Batmanglij                        57631                      13691   \n",
       "Zoran Lisinac                           330                       1087   \n",
       "Álex de la Iglesia                    22753                        940   \n",
       "Émile Gaudreault                       5548                       1033   \n",
       "Éric Tessier                           1003                         79   \n",
       "Étienne Faure                           569                         19   \n",
       "\n",
       "                            facenumber_in_poster  num_user_for_reviews  \\\n",
       "director_name                                                            \n",
       "A. Raven Cruz                                2.0                   9.0   \n",
       "Aaron Hann                                   0.0                  59.0   \n",
       "Aaron Schneider                              1.0                  97.0   \n",
       "Aaron Seltzer                                0.0                 613.0   \n",
       "Abel Ferrara                                 3.0                  48.0   \n",
       "Adam Brooks                                  5.0                 168.0   \n",
       "Adam Carolla                                 0.0                  11.0   \n",
       "Adam Goldberg                                2.0                  40.0   \n",
       "Adam Green                                   0.0                 235.0   \n",
       "Adam Jay Epstein                             6.0                  35.0   \n",
       "Adam Marcus                                  0.0                 317.0   \n",
       "Adam McKay                                  20.0                2327.0   \n",
       "Adam Rapp                                    4.0                  53.0   \n",
       "Adam Rifkin                                  0.0                 195.0   \n",
       "Adam Shankman                               27.0                2653.0   \n",
       "Adrian Lyne                                  0.0                 980.0   \n",
       "Adrienne Shelly                              1.0                 204.0   \n",
       "Agnieszka Holland                            0.0                  86.0   \n",
       "Agnieszka Wojtowicz-Vosloo                   1.0                 137.0   \n",
       "Agustín Díaz Yanes                           1.0                  84.0   \n",
       "Aki Kaurismäki                               1.0                  41.0   \n",
       "Akira Kurosawa                               6.0                 636.0   \n",
       "Akiva Goldsman                               0.0                 126.0   \n",
       "Akiva Schaffer                              13.0                 563.0   \n",
       "Al Franklin                                  0.0                   2.0   \n",
       "Al Silliman Jr.                              0.0                   5.0   \n",
       "Alain Resnais                                0.0                  31.0   \n",
       "Alan Alda                                    2.0                  33.0   \n",
       "Alan Cohn                                    0.0                 106.0   \n",
       "Alan J. Pakula                               0.0                 203.0   \n",
       "...                                          ...                   ...   \n",
       "William Phillips                             1.0                  27.0   \n",
       "William Sachs                                0.0                  44.0   \n",
       "William Shatner                              1.0                 293.0   \n",
       "William Wyler                                5.0                 235.0   \n",
       "Wilson Yip                                   0.0                  45.0   \n",
       "Wolfgang Becker                              2.0                 225.0   \n",
       "Wolfgang Petersen                            7.0                4335.0   \n",
       "Woo-Suk Kang                                 0.0                  17.0   \n",
       "Woody Allen                                 22.0                4820.0   \n",
       "Wych Kaosayananda                            1.0                 277.0   \n",
       "Xavier Beauvois                              0.0                  89.0   \n",
       "Xavier Gens                                  5.0                 602.0   \n",
       "Yarrow Cheney                                0.0                 155.0   \n",
       "Yash Chopra                                  4.0                 405.0   \n",
       "Yimou Zhang                                 18.0                2521.0   \n",
       "Yorgos Lanthimos                             0.0                 170.0   \n",
       "Youssef Delara                               1.0                  20.0   \n",
       "Yuefeng Song                                 0.0                  18.0   \n",
       "Zach Braff                                   7.0                1071.0   \n",
       "Zach Cregger                                 2.0                  73.0   \n",
       "Zack Snyder                                  6.0               12048.0   \n",
       "Zack Ward                                    0.0                   6.0   \n",
       "Zackary Adler                                0.0                  26.0   \n",
       "Zak Penn                                     0.0                  63.0   \n",
       "Zal Batmanglij                               4.0                 188.0   \n",
       "Zoran Lisinac                                3.0                   2.0   \n",
       "Álex de la Iglesia                           4.0                  94.0   \n",
       "Émile Gaudreault                             0.0                  67.0   \n",
       "Éric Tessier                                 0.0                   5.0   \n",
       "Étienne Faure                                0.0                   1.0   \n",
       "\n",
       "                                 budget  title_year  actor_2_facebook_likes  \\\n",
       "director_name                                                                 \n",
       "A. Raven Cruz                 1000000.0      2005.0                   361.0   \n",
       "Aaron Hann                          0.0      2015.0                   152.0   \n",
       "Aaron Schneider               7500000.0      2009.0                  3000.0   \n",
       "Aaron Seltzer                20000000.0      2006.0                   869.0   \n",
       "Abel Ferrara                 12500000.0      1996.0                   787.0   \n",
       "Adam Brooks                         0.0      2008.0                   109.0   \n",
       "Adam Carolla                  1500000.0      2015.0                   485.0   \n",
       "Adam Goldberg                 1650000.0      2003.0                   163.0   \n",
       "Adam Green                    1500000.0      2006.0                   935.0   \n",
       "Adam Jay Epstein                    0.0      2008.0                   295.0   \n",
       "Adam Marcus                   2500000.0      1993.0                   805.0   \n",
       "Adam McKay                  342000000.0     12056.0                 51000.0   \n",
       "Adam Rapp                     3500000.0      2005.0                  8000.0   \n",
       "Adam Rifkin                  15250000.0      4014.0                   941.0   \n",
       "Adam Shankman               425000000.0     16043.0                  8181.0   \n",
       "Adrian Lyne                  85000000.0      7958.0                  1110.0   \n",
       "Adrienne Shelly               2000000.0      2007.0                   541.0   \n",
       "Agnieszka Holland            11000000.0      2006.0                    35.0   \n",
       "Agnieszka Wojtowicz-Vosloo    4500000.0      2009.0                  1000.0   \n",
       "Agustín Díaz Yanes           24000000.0      2006.0                  1000.0   \n",
       "Aki Kaurismäki                3850000.0      2011.0                    67.0   \n",
       "Akira Kurosawa               13900000.0      3947.0                    14.0   \n",
       "Akiva Goldsman               60000000.0      2014.0                   882.0   \n",
       "Akiva Schaffer              136000000.0      6031.0                  1616.0   \n",
       "Al Franklin                    300000.0      2015.0                   320.0   \n",
       "Al Silliman Jr.                100000.0      1969.0                    12.0   \n",
       "Alain Resnais                       0.0      2009.0                    74.0   \n",
       "Alan Alda                           0.0      1981.0                   167.0   \n",
       "Alan Cohn                    14000000.0      1998.0                  2000.0   \n",
       "Alan J. Pakula              131000000.0      3990.0                 19000.0   \n",
       "...                                 ...         ...                     ...   \n",
       "William Phillips             10000000.0      2010.0                   716.0   \n",
       "William Sachs                       0.0      1980.0                   110.0   \n",
       "William Shatner              27800000.0      1989.0                   664.0   \n",
       "William Wyler                 2100000.0      1946.0                   208.0   \n",
       "Wilson Yip                   36000000.0      2015.0                    79.0   \n",
       "Wolfgang Becker               4800000.0      2003.0                    51.0   \n",
       "Wolfgang Petersen           651000000.0     13967.0                 28971.0   \n",
       "Woo-Suk Kang                  8000000.0      2003.0                    15.0   \n",
       "Woody Allen                 314500000.0     43934.0                 27437.0   \n",
       "Wych Kaosayananda            70000000.0      2002.0                   324.0   \n",
       "Xavier Beauvois               4000000.0      2010.0                   135.0   \n",
       "Xavier Gens                  27000000.0      4018.0                  1477.0   \n",
       "Yarrow Cheney                75000000.0      2016.0                   904.0   \n",
       "Yash Chopra                  14217600.0      4016.0                  3860.0   \n",
       "Yimou Zhang                 301000000.0     16057.0                  2035.0   \n",
       "Yorgos Lanthimos                    0.0      2009.0                    37.0   \n",
       "Youssef Delara                1227000.0      4025.0                   960.0   \n",
       "Yuefeng Song                 40000000.0      2014.0                    47.0   \n",
       "Zach Braff                    8500000.0      4018.0                  1379.0   \n",
       "Zach Cregger                  6000000.0      2009.0                   308.0   \n",
       "Zack Snyder                 884000000.0     16073.0                 27398.0   \n",
       "Zack Ward                           0.0      2016.0                   290.0   \n",
       "Zackary Adler                 2500000.0      2015.0                   159.0   \n",
       "Zak Penn                      1400000.0      2004.0                    70.0   \n",
       "Zal Batmanglij                6500000.0      4024.0                  1037.0   \n",
       "Zoran Lisinac                  250000.0      2013.0                   297.0   \n",
       "Álex de la Iglesia           10000000.0      2008.0                   161.0   \n",
       "Émile Gaudreault              5000000.0      2003.0                   210.0   \n",
       "Éric Tessier                  3200000.0      2003.0                    16.0   \n",
       "Étienne Faure                  500000.0      2015.0                     0.0   \n",
       "\n",
       "                            imdb_score  aspect_ratio  movie_facebook_likes  \n",
       "director_name                                                               \n",
       "A. Raven Cruz                      1.9          1.78                   128  \n",
       "Aaron Hann                         6.0          0.00                     0  \n",
       "Aaron Schneider                    7.1          2.35                     0  \n",
       "Aaron Seltzer                      2.7          1.85                   806  \n",
       "Abel Ferrara                       6.6          1.85                   344  \n",
       "Adam Brooks                        7.2          2.35                     0  \n",
       "Adam Carolla                       6.1          0.00                   212  \n",
       "Adam Goldberg                      5.4          2.35                    63  \n",
       "Adam Green                         5.7          1.85                     0  \n",
       "Adam Jay Epstein                   3.8          1.85                   636  \n",
       "Adam Marcus                        4.3          1.85                   949  \n",
       "Adam McKay                        41.5         13.60                156000  \n",
       "Adam Rapp                          6.4          1.85                   414  \n",
       "Adam Rifkin                       13.0          2.35                    47  \n",
       "Adam Shankman                     47.7         18.80                 53581  \n",
       "Adrian Lyne                       25.6          7.40                  3000  \n",
       "Adrienne Shelly                    7.1          1.85                     0  \n",
       "Agnieszka Holland                  6.8          2.35                     0  \n",
       "Agnieszka Wojtowicz-Vosloo         5.9          2.35                  7000  \n",
       "Agustín Díaz Yanes                 6.1          1.85                     0  \n",
       "Aki Kaurismäki                     7.2          1.85                     0  \n",
       "Akira Kurosawa                    16.2          3.22                 11355  \n",
       "Akiva Goldsman                     6.2          2.35                 17000  \n",
       "Akiva Schaffer                    18.1          7.05                 30000  \n",
       "Al Franklin                        4.3         16.00                    85  \n",
       "Al Silliman Jr.                    4.0          1.37                    17  \n",
       "Alain Resnais                      6.3          2.35                   512  \n",
       "Alan Alda                          7.2          1.85                   337  \n",
       "Alan Cohn                          6.0          1.85                   645  \n",
       "Alan J. Pakula                    12.6          4.70                   979  \n",
       "...                                ...           ...                   ...  \n",
       "William Phillips                   6.5          2.35                   850  \n",
       "William Sachs                      3.4          2.35                   438  \n",
       "William Shatner                    5.4          2.35                     0  \n",
       "William Wyler                      8.1          1.37                     0  \n",
       "Wilson Yip                         7.2          2.35                 12000  \n",
       "Wolfgang Becker                    7.7          1.85                 11000  \n",
       "Wolfgang Petersen                 48.0         15.45                 32000  \n",
       "Woo-Suk Kang                       7.2          2.35                   387  \n",
       "Woody Allen                      154.2         40.07                161735  \n",
       "Wych Kaosayananda                  3.6          2.35                   391  \n",
       "Xavier Beauvois                    7.2          2.35                     0  \n",
       "Xavier Gens                       12.1          4.70                     0  \n",
       "Yarrow Cheney                      6.8          1.85                 36000  \n",
       "Yash Chopra                       14.8          4.70                 14000  \n",
       "Yimou Zhang                       56.7         18.80                 14568  \n",
       "Yorgos Lanthimos                   7.3          2.35                 13000  \n",
       "Youssef Delara                    10.9          4.70                   406  \n",
       "Yuefeng Song                       6.4          0.00                     0  \n",
       "Zach Braff                        14.3          4.70                     0  \n",
       "Zach Cregger                       5.1          1.85                   985  \n",
       "Zack Snyder                       57.4         18.80                418000  \n",
       "Zack Ward                          4.0          0.00                   378  \n",
       "Zackary Adler                      5.0          0.00                     0  \n",
       "Zak Penn                           6.6          1.85                   400  \n",
       "Zal Batmanglij                    13.6          4.20                 12000  \n",
       "Zoran Lisinac                      7.1          1.85                   231  \n",
       "Álex de la Iglesia                 6.1          2.35                     0  \n",
       "Émile Gaudreault                   6.7          1.85                   352  \n",
       "Éric Tessier                       6.6          1.85                    39  \n",
       "Étienne Faure                      4.3          1.78                   114  \n",
       "\n",
       "[2398 rows x 16 columns]"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped.mean()\n",
    "grouped.sum()\n",
    "#grouped.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "director_name\n",
       "A. Raven Cruz                   97.0\n",
       "Aaron Hann                      87.0\n",
       "Aaron Schneider                100.0\n",
       "Aaron Seltzer                   85.0\n",
       "Abel Ferrara                    99.0\n",
       "Adam Brooks                    112.0\n",
       "Adam Carolla                    98.0\n",
       "Adam Goldberg                  111.0\n",
       "Adam Green                      93.0\n",
       "Adam Jay Epstein                76.0\n",
       "Adam Marcus                     91.0\n",
       "Adam McKay                     715.0\n",
       "Adam Rapp                       98.0\n",
       "Adam Rifkin                    190.0\n",
       "Adam Shankman                  850.0\n",
       "Adrian Lyne                    450.0\n",
       "Adrienne Shelly                108.0\n",
       "Agnieszka Holland              104.0\n",
       "Agnieszka Wojtowicz-Vosloo     104.0\n",
       "Agustín Díaz Yanes             145.0\n",
       "Aki Kaurismäki                  93.0\n",
       "Akira Kurosawa                 336.0\n",
       "Akiva Goldsman                 118.0\n",
       "Akiva Schaffer                 292.0\n",
       "Al Franklin                     96.0\n",
       "Al Silliman Jr.                 93.0\n",
       "Alain Resnais                  104.0\n",
       "Alan Alda                      107.0\n",
       "Alan Cohn                       96.0\n",
       "Alan J. Pakula                 252.0\n",
       "                               ...  \n",
       "William Phillips                89.0\n",
       "William Sachs                   95.0\n",
       "William Shatner                107.0\n",
       "William Wyler                  172.0\n",
       "Wilson Yip                     105.0\n",
       "Wolfgang Becker                121.0\n",
       "Wolfgang Petersen             1062.0\n",
       "Woo-Suk Kang                   135.0\n",
       "Woody Allen                   2194.0\n",
       "Wych Kaosayananda               91.0\n",
       "Xavier Beauvois                122.0\n",
       "Xavier Gens                    216.0\n",
       "Yarrow Cheney                   87.0\n",
       "Yash Chopra                    368.0\n",
       "Yimou Zhang                    838.0\n",
       "Yorgos Lanthimos                94.0\n",
       "Youssef Delara                 168.0\n",
       "Yuefeng Song                    88.0\n",
       "Zach Braff                     208.0\n",
       "Zach Cregger                    90.0\n",
       "Zack Snyder                   1107.0\n",
       "Zack Ward                       92.0\n",
       "Zackary Adler                  110.0\n",
       "Zak Penn                        94.0\n",
       "Zal Batmanglij                 201.0\n",
       "Zoran Lisinac                  108.0\n",
       "Álex de la Iglesia             104.0\n",
       "Émile Gaudreault                92.0\n",
       "Éric Tessier                    99.0\n",
       "Étienne Faure                   98.0\n",
       "Name: duration, Length: 2398, dtype: float64"
      ]
     },
     "execution_count": 139,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 只针对某个特征进行计算\n",
    "grouped['duration'].sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mean</th>\n",
       "      <th>sum</th>\n",
       "      <th>std</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>director_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A. Raven Cruz</th>\n",
       "      <td>97.000000</td>\n",
       "      <td>97.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aaron Hann</th>\n",
       "      <td>87.000000</td>\n",
       "      <td>87.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aaron Schneider</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>100.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aaron Seltzer</th>\n",
       "      <td>85.000000</td>\n",
       "      <td>85.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Abel Ferrara</th>\n",
       "      <td>99.000000</td>\n",
       "      <td>99.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Brooks</th>\n",
       "      <td>112.000000</td>\n",
       "      <td>112.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Carolla</th>\n",
       "      <td>98.000000</td>\n",
       "      <td>98.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Goldberg</th>\n",
       "      <td>111.000000</td>\n",
       "      <td>111.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Green</th>\n",
       "      <td>93.000000</td>\n",
       "      <td>93.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Jay Epstein</th>\n",
       "      <td>76.000000</td>\n",
       "      <td>76.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Marcus</th>\n",
       "      <td>91.000000</td>\n",
       "      <td>91.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam McKay</th>\n",
       "      <td>119.166667</td>\n",
       "      <td>715.0</td>\n",
       "      <td>16.277797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Rapp</th>\n",
       "      <td>98.000000</td>\n",
       "      <td>98.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Rifkin</th>\n",
       "      <td>95.000000</td>\n",
       "      <td>190.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Shankman</th>\n",
       "      <td>106.250000</td>\n",
       "      <td>850.0</td>\n",
       "      <td>13.987239</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adrian Lyne</th>\n",
       "      <td>112.500000</td>\n",
       "      <td>450.0</td>\n",
       "      <td>12.662280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adrienne Shelly</th>\n",
       "      <td>108.000000</td>\n",
       "      <td>108.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agnieszka Holland</th>\n",
       "      <td>104.000000</td>\n",
       "      <td>104.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agnieszka Wojtowicz-Vosloo</th>\n",
       "      <td>104.000000</td>\n",
       "      <td>104.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agustín Díaz Yanes</th>\n",
       "      <td>145.000000</td>\n",
       "      <td>145.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aki Kaurismäki</th>\n",
       "      <td>93.000000</td>\n",
       "      <td>93.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Akira Kurosawa</th>\n",
       "      <td>168.000000</td>\n",
       "      <td>336.0</td>\n",
       "      <td>48.083261</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Akiva Goldsman</th>\n",
       "      <td>118.000000</td>\n",
       "      <td>118.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Akiva Schaffer</th>\n",
       "      <td>97.333333</td>\n",
       "      <td>292.0</td>\n",
       "      <td>8.082904</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Al Franklin</th>\n",
       "      <td>96.000000</td>\n",
       "      <td>96.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Al Silliman Jr.</th>\n",
       "      <td>93.000000</td>\n",
       "      <td>93.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alain Resnais</th>\n",
       "      <td>104.000000</td>\n",
       "      <td>104.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alan Alda</th>\n",
       "      <td>107.000000</td>\n",
       "      <td>107.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alan Cohn</th>\n",
       "      <td>96.000000</td>\n",
       "      <td>96.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alan J. Pakula</th>\n",
       "      <td>126.000000</td>\n",
       "      <td>252.0</td>\n",
       "      <td>21.213203</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Phillips</th>\n",
       "      <td>89.000000</td>\n",
       "      <td>89.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Sachs</th>\n",
       "      <td>95.000000</td>\n",
       "      <td>95.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Shatner</th>\n",
       "      <td>107.000000</td>\n",
       "      <td>107.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Wyler</th>\n",
       "      <td>172.000000</td>\n",
       "      <td>172.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson Yip</th>\n",
       "      <td>105.000000</td>\n",
       "      <td>105.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wolfgang Becker</th>\n",
       "      <td>121.000000</td>\n",
       "      <td>121.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wolfgang Petersen</th>\n",
       "      <td>151.714286</td>\n",
       "      <td>1062.0</td>\n",
       "      <td>70.698218</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Woo-Suk Kang</th>\n",
       "      <td>135.000000</td>\n",
       "      <td>135.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Woody Allen</th>\n",
       "      <td>99.727273</td>\n",
       "      <td>2194.0</td>\n",
       "      <td>10.788803</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wych Kaosayananda</th>\n",
       "      <td>91.000000</td>\n",
       "      <td>91.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Xavier Beauvois</th>\n",
       "      <td>122.000000</td>\n",
       "      <td>122.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Xavier Gens</th>\n",
       "      <td>108.000000</td>\n",
       "      <td>216.0</td>\n",
       "      <td>19.798990</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yarrow Cheney</th>\n",
       "      <td>87.000000</td>\n",
       "      <td>87.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yash Chopra</th>\n",
       "      <td>184.000000</td>\n",
       "      <td>368.0</td>\n",
       "      <td>11.313708</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yimou Zhang</th>\n",
       "      <td>104.750000</td>\n",
       "      <td>838.0</td>\n",
       "      <td>22.114959</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yorgos Lanthimos</th>\n",
       "      <td>94.000000</td>\n",
       "      <td>94.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Youssef Delara</th>\n",
       "      <td>84.000000</td>\n",
       "      <td>168.0</td>\n",
       "      <td>5.656854</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yuefeng Song</th>\n",
       "      <td>88.000000</td>\n",
       "      <td>88.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zach Braff</th>\n",
       "      <td>104.000000</td>\n",
       "      <td>208.0</td>\n",
       "      <td>2.828427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zach Cregger</th>\n",
       "      <td>90.000000</td>\n",
       "      <td>90.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zack Snyder</th>\n",
       "      <td>138.375000</td>\n",
       "      <td>1107.0</td>\n",
       "      <td>40.454339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zack Ward</th>\n",
       "      <td>92.000000</td>\n",
       "      <td>92.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zackary Adler</th>\n",
       "      <td>110.000000</td>\n",
       "      <td>110.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zak Penn</th>\n",
       "      <td>94.000000</td>\n",
       "      <td>94.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zal Batmanglij</th>\n",
       "      <td>100.500000</td>\n",
       "      <td>201.0</td>\n",
       "      <td>21.920310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoran Lisinac</th>\n",
       "      <td>108.000000</td>\n",
       "      <td>108.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Álex de la Iglesia</th>\n",
       "      <td>104.000000</td>\n",
       "      <td>104.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Émile Gaudreault</th>\n",
       "      <td>92.000000</td>\n",
       "      <td>92.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Éric Tessier</th>\n",
       "      <td>99.000000</td>\n",
       "      <td>99.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Étienne Faure</th>\n",
       "      <td>98.000000</td>\n",
       "      <td>98.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2398 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  mean     sum        std\n",
       "director_name                                            \n",
       "A. Raven Cruz                97.000000    97.0        NaN\n",
       "Aaron Hann                   87.000000    87.0        NaN\n",
       "Aaron Schneider             100.000000   100.0        NaN\n",
       "Aaron Seltzer                85.000000    85.0        NaN\n",
       "Abel Ferrara                 99.000000    99.0        NaN\n",
       "Adam Brooks                 112.000000   112.0        NaN\n",
       "Adam Carolla                 98.000000    98.0        NaN\n",
       "Adam Goldberg               111.000000   111.0        NaN\n",
       "Adam Green                   93.000000    93.0        NaN\n",
       "Adam Jay Epstein             76.000000    76.0        NaN\n",
       "Adam Marcus                  91.000000    91.0        NaN\n",
       "Adam McKay                  119.166667   715.0  16.277797\n",
       "Adam Rapp                    98.000000    98.0        NaN\n",
       "Adam Rifkin                  95.000000   190.0   0.000000\n",
       "Adam Shankman               106.250000   850.0  13.987239\n",
       "Adrian Lyne                 112.500000   450.0  12.662280\n",
       "Adrienne Shelly             108.000000   108.0        NaN\n",
       "Agnieszka Holland           104.000000   104.0        NaN\n",
       "Agnieszka Wojtowicz-Vosloo  104.000000   104.0        NaN\n",
       "Agustín Díaz Yanes          145.000000   145.0        NaN\n",
       "Aki Kaurismäki               93.000000    93.0        NaN\n",
       "Akira Kurosawa              168.000000   336.0  48.083261\n",
       "Akiva Goldsman              118.000000   118.0        NaN\n",
       "Akiva Schaffer               97.333333   292.0   8.082904\n",
       "Al Franklin                  96.000000    96.0        NaN\n",
       "Al Silliman Jr.              93.000000    93.0        NaN\n",
       "Alain Resnais               104.000000   104.0        NaN\n",
       "Alan Alda                   107.000000   107.0        NaN\n",
       "Alan Cohn                    96.000000    96.0        NaN\n",
       "Alan J. Pakula              126.000000   252.0  21.213203\n",
       "...                                ...     ...        ...\n",
       "William Phillips             89.000000    89.0        NaN\n",
       "William Sachs                95.000000    95.0        NaN\n",
       "William Shatner             107.000000   107.0        NaN\n",
       "William Wyler               172.000000   172.0        NaN\n",
       "Wilson Yip                  105.000000   105.0        NaN\n",
       "Wolfgang Becker             121.000000   121.0        NaN\n",
       "Wolfgang Petersen           151.714286  1062.0  70.698218\n",
       "Woo-Suk Kang                135.000000   135.0        NaN\n",
       "Woody Allen                  99.727273  2194.0  10.788803\n",
       "Wych Kaosayananda            91.000000    91.0        NaN\n",
       "Xavier Beauvois             122.000000   122.0        NaN\n",
       "Xavier Gens                 108.000000   216.0  19.798990\n",
       "Yarrow Cheney                87.000000    87.0        NaN\n",
       "Yash Chopra                 184.000000   368.0  11.313708\n",
       "Yimou Zhang                 104.750000   838.0  22.114959\n",
       "Yorgos Lanthimos             94.000000    94.0        NaN\n",
       "Youssef Delara               84.000000   168.0   5.656854\n",
       "Yuefeng Song                 88.000000    88.0        NaN\n",
       "Zach Braff                  104.000000   208.0   2.828427\n",
       "Zach Cregger                 90.000000    90.0        NaN\n",
       "Zack Snyder                 138.375000  1107.0  40.454339\n",
       "Zack Ward                    92.000000    92.0        NaN\n",
       "Zackary Adler               110.000000   110.0        NaN\n",
       "Zak Penn                     94.000000    94.0        NaN\n",
       "Zal Batmanglij              100.500000   201.0  21.920310\n",
       "Zoran Lisinac               108.000000   108.0        NaN\n",
       "Álex de la Iglesia          104.000000   104.0        NaN\n",
       "Émile Gaudreault             92.000000    92.0        NaN\n",
       "Éric Tessier                 99.000000    99.0        NaN\n",
       "Étienne Faure                98.000000    98.0        NaN\n",
       "\n",
       "[2398 rows x 3 columns]"
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 使用agg函数进行多个统计量计算\n",
    "import numpy as np \n",
    "grouped['duration'].agg([np.mean,np.sum,np.std])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>color</th>\n",
       "      <th>director_name</th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>duration</th>\n",
       "      <th>director_facebook_likes</th>\n",
       "      <th>actor_3_facebook_likes</th>\n",
       "      <th>actor_2_name</th>\n",
       "      <th>actor_1_facebook_likes</th>\n",
       "      <th>gross</th>\n",
       "      <th>genres</th>\n",
       "      <th>...</th>\n",
       "      <th>num_user_for_reviews</th>\n",
       "      <th>language</th>\n",
       "      <th>country</th>\n",
       "      <th>content_rating</th>\n",
       "      <th>budget</th>\n",
       "      <th>title_year</th>\n",
       "      <th>actor_2_facebook_likes</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Color</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>723.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>855.0</td>\n",
       "      <td>Joel David Moore</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>760505847.0</td>\n",
       "      <td>Action|Adventure|Fantasy|Sci-Fi</td>\n",
       "      <td>...</td>\n",
       "      <td>3054.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>237000000.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>7.9</td>\n",
       "      <td>1.78</td>\n",
       "      <td>33000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Color</td>\n",
       "      <td>Gore Verbinski</td>\n",
       "      <td>302.0</td>\n",
       "      <td>169.0</td>\n",
       "      <td>563.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>Orlando Bloom</td>\n",
       "      <td>40000.0</td>\n",
       "      <td>309404152.0</td>\n",
       "      <td>Action|Adventure|Fantasy</td>\n",
       "      <td>...</td>\n",
       "      <td>1238.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>300000000.0</td>\n",
       "      <td>2007.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Color</td>\n",
       "      <td>Sam Mendes</td>\n",
       "      <td>602.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>Rory Kinnear</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>200074175.0</td>\n",
       "      <td>Action|Adventure|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>994.0</td>\n",
       "      <td>English</td>\n",
       "      <td>UK</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>245000000.0</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>393.0</td>\n",
       "      <td>6.8</td>\n",
       "      <td>2.35</td>\n",
       "      <td>85000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Color</td>\n",
       "      <td>Christopher Nolan</td>\n",
       "      <td>813.0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>22000.0</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>Christian Bale</td>\n",
       "      <td>27000.0</td>\n",
       "      <td>448130642.0</td>\n",
       "      <td>Action|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>2701.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>250000000.0</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>23000.0</td>\n",
       "      <td>8.5</td>\n",
       "      <td>2.35</td>\n",
       "      <td>164000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>Doug Walker</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>131.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Rob Walker</td>\n",
       "      <td>131.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Documentary</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>12.0</td>\n",
       "      <td>7.1</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "   color      director_name  num_critic_for_reviews  duration  \\\n",
       "0  Color      James Cameron                   723.0     178.0   \n",
       "1  Color     Gore Verbinski                   302.0     169.0   \n",
       "2  Color         Sam Mendes                   602.0     148.0   \n",
       "3  Color  Christopher Nolan                   813.0     164.0   \n",
       "4    NaN        Doug Walker                     NaN       NaN   \n",
       "\n",
       "   director_facebook_likes  actor_3_facebook_likes      actor_2_name  \\\n",
       "0                      0.0                   855.0  Joel David Moore   \n",
       "1                    563.0                  1000.0     Orlando Bloom   \n",
       "2                      0.0                   161.0      Rory Kinnear   \n",
       "3                  22000.0                 23000.0    Christian Bale   \n",
       "4                    131.0                     NaN        Rob Walker   \n",
       "\n",
       "   actor_1_facebook_likes        gross                           genres  \\\n",
       "0                  1000.0  760505847.0  Action|Adventure|Fantasy|Sci-Fi   \n",
       "1                 40000.0  309404152.0         Action|Adventure|Fantasy   \n",
       "2                 11000.0  200074175.0        Action|Adventure|Thriller   \n",
       "3                 27000.0  448130642.0                  Action|Thriller   \n",
       "4                   131.0          NaN                      Documentary   \n",
       "\n",
       "          ...          num_user_for_reviews language  country  content_rating  \\\n",
       "0         ...                        3054.0  English      USA           PG-13   \n",
       "1         ...                        1238.0  English      USA           PG-13   \n",
       "2         ...                         994.0  English       UK           PG-13   \n",
       "3         ...                        2701.0  English      USA           PG-13   \n",
       "4         ...                           NaN      NaN      NaN             NaN   \n",
       "\n",
       "        budget  title_year actor_2_facebook_likes imdb_score  aspect_ratio  \\\n",
       "0  237000000.0      2009.0                  936.0        7.9          1.78   \n",
       "1  300000000.0      2007.0                 5000.0        7.1          2.35   \n",
       "2  245000000.0      2015.0                  393.0        6.8          2.35   \n",
       "3  250000000.0      2012.0                23000.0        8.5          2.35   \n",
       "4          NaN         NaN                   12.0        7.1           NaN   \n",
       "\n",
       "  movie_facebook_likes  \n",
       "0                33000  \n",
       "1                    0  \n",
       "2                85000  \n",
       "3               164000  \n",
       "4                    0  \n",
       "\n",
       "[5 rows x 28 columns]"
      ]
     },
     "execution_count": 143,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>duration</th>\n",
       "      <th>director_facebook_likes</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>director_name</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>A. Raven Cruz</th>\n",
       "      <td>97.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aaron Hann</th>\n",
       "      <td>87.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aaron Schneider</th>\n",
       "      <td>100.000000</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aaron Seltzer</th>\n",
       "      <td>85.000000</td>\n",
       "      <td>64.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Abel Ferrara</th>\n",
       "      <td>99.000000</td>\n",
       "      <td>220.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Brooks</th>\n",
       "      <td>112.000000</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Carolla</th>\n",
       "      <td>98.000000</td>\n",
       "      <td>102.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Goldberg</th>\n",
       "      <td>111.000000</td>\n",
       "      <td>1000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Green</th>\n",
       "      <td>93.000000</td>\n",
       "      <td>134.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Jay Epstein</th>\n",
       "      <td>76.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Marcus</th>\n",
       "      <td>91.000000</td>\n",
       "      <td>18.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam McKay</th>\n",
       "      <td>119.166667</td>\n",
       "      <td>1710.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Rapp</th>\n",
       "      <td>98.000000</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Rifkin</th>\n",
       "      <td>95.000000</td>\n",
       "      <td>178.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adam Shankman</th>\n",
       "      <td>106.250000</td>\n",
       "      <td>1304.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adrian Lyne</th>\n",
       "      <td>112.500000</td>\n",
       "      <td>852.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Adrienne Shelly</th>\n",
       "      <td>108.000000</td>\n",
       "      <td>191.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agnieszka Holland</th>\n",
       "      <td>104.000000</td>\n",
       "      <td>238.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agnieszka Wojtowicz-Vosloo</th>\n",
       "      <td>104.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agustín Díaz Yanes</th>\n",
       "      <td>145.000000</td>\n",
       "      <td>13.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Aki Kaurismäki</th>\n",
       "      <td>93.000000</td>\n",
       "      <td>592.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Akira Kurosawa</th>\n",
       "      <td>168.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Akiva Goldsman</th>\n",
       "      <td>118.000000</td>\n",
       "      <td>167.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Akiva Schaffer</th>\n",
       "      <td>97.333333</td>\n",
       "      <td>246.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Al Franklin</th>\n",
       "      <td>96.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Al Silliman Jr.</th>\n",
       "      <td>93.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alain Resnais</th>\n",
       "      <td>104.000000</td>\n",
       "      <td>752.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alan Alda</th>\n",
       "      <td>107.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alan Cohn</th>\n",
       "      <td>96.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Alan J. Pakula</th>\n",
       "      <td>126.000000</td>\n",
       "      <td>158.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Phillips</th>\n",
       "      <td>89.000000</td>\n",
       "      <td>3.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Sachs</th>\n",
       "      <td>95.000000</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Shatner</th>\n",
       "      <td>107.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Wyler</th>\n",
       "      <td>172.000000</td>\n",
       "      <td>355.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson Yip</th>\n",
       "      <td>105.000000</td>\n",
       "      <td>25.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wolfgang Becker</th>\n",
       "      <td>121.000000</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wolfgang Petersen</th>\n",
       "      <td>151.714286</td>\n",
       "      <td>1743.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Woo-Suk Kang</th>\n",
       "      <td>135.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Woody Allen</th>\n",
       "      <td>99.727273</td>\n",
       "      <td>242000.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wych Kaosayananda</th>\n",
       "      <td>91.000000</td>\n",
       "      <td>8.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Xavier Beauvois</th>\n",
       "      <td>122.000000</td>\n",
       "      <td>22.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Xavier Gens</th>\n",
       "      <td>108.000000</td>\n",
       "      <td>174.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yarrow Cheney</th>\n",
       "      <td>87.000000</td>\n",
       "      <td>11.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yash Chopra</th>\n",
       "      <td>184.000000</td>\n",
       "      <td>294.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yimou Zhang</th>\n",
       "      <td>104.750000</td>\n",
       "      <td>4888.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yorgos Lanthimos</th>\n",
       "      <td>94.000000</td>\n",
       "      <td>252.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Youssef Delara</th>\n",
       "      <td>84.000000</td>\n",
       "      <td>16.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yuefeng Song</th>\n",
       "      <td>88.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zach Braff</th>\n",
       "      <td>104.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zach Cregger</th>\n",
       "      <td>90.000000</td>\n",
       "      <td>138.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zack Snyder</th>\n",
       "      <td>138.375000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zack Ward</th>\n",
       "      <td>92.000000</td>\n",
       "      <td>662.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zackary Adler</th>\n",
       "      <td>110.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zak Penn</th>\n",
       "      <td>94.000000</td>\n",
       "      <td>87.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zal Batmanglij</th>\n",
       "      <td>100.500000</td>\n",
       "      <td>258.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoran Lisinac</th>\n",
       "      <td>108.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Álex de la Iglesia</th>\n",
       "      <td>104.000000</td>\n",
       "      <td>275.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Émile Gaudreault</th>\n",
       "      <td>92.000000</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Éric Tessier</th>\n",
       "      <td>99.000000</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Étienne Faure</th>\n",
       "      <td>98.000000</td>\n",
       "      <td>77.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2398 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                              duration  director_facebook_likes\n",
       "director_name                                                  \n",
       "A. Raven Cruz                97.000000                      0.0\n",
       "Aaron Hann                   87.000000                      0.0\n",
       "Aaron Schneider             100.000000                     11.0\n",
       "Aaron Seltzer                85.000000                     64.0\n",
       "Abel Ferrara                 99.000000                    220.0\n",
       "Adam Brooks                 112.000000                     20.0\n",
       "Adam Carolla                 98.000000                    102.0\n",
       "Adam Goldberg               111.000000                   1000.0\n",
       "Adam Green                   93.000000                    134.0\n",
       "Adam Jay Epstein             76.000000                      0.0\n",
       "Adam Marcus                  91.000000                     18.0\n",
       "Adam McKay                  119.166667                   1710.0\n",
       "Adam Rapp                    98.000000                      9.0\n",
       "Adam Rifkin                  95.000000                    178.0\n",
       "Adam Shankman               106.250000                   1304.0\n",
       "Adrian Lyne                 112.500000                    852.0\n",
       "Adrienne Shelly             108.000000                    191.0\n",
       "Agnieszka Holland           104.000000                    238.0\n",
       "Agnieszka Wojtowicz-Vosloo  104.000000                      0.0\n",
       "Agustín Díaz Yanes          145.000000                     13.0\n",
       "Aki Kaurismäki               93.000000                    592.0\n",
       "Akira Kurosawa              168.000000                      0.0\n",
       "Akiva Goldsman              118.000000                    167.0\n",
       "Akiva Schaffer               97.333333                    246.0\n",
       "Al Franklin                  96.000000                      0.0\n",
       "Al Silliman Jr.              93.000000                      0.0\n",
       "Alain Resnais               104.000000                    752.0\n",
       "Alan Alda                   107.000000                      0.0\n",
       "Alan Cohn                    96.000000                      0.0\n",
       "Alan J. Pakula              126.000000                    158.0\n",
       "...                                ...                      ...\n",
       "William Phillips             89.000000                      3.0\n",
       "William Sachs                95.000000                     14.0\n",
       "William Shatner             107.000000                      0.0\n",
       "William Wyler               172.000000                    355.0\n",
       "Wilson Yip                  105.000000                     25.0\n",
       "Wolfgang Becker             121.000000                     31.0\n",
       "Wolfgang Petersen           151.714286                   1743.0\n",
       "Woo-Suk Kang                135.000000                      0.0\n",
       "Woody Allen                  99.727273                 242000.0\n",
       "Wych Kaosayananda            91.000000                      8.0\n",
       "Xavier Beauvois             122.000000                     22.0\n",
       "Xavier Gens                 108.000000                    174.0\n",
       "Yarrow Cheney                87.000000                     11.0\n",
       "Yash Chopra                 184.000000                    294.0\n",
       "Yimou Zhang                 104.750000                   4888.0\n",
       "Yorgos Lanthimos             94.000000                    252.0\n",
       "Youssef Delara               84.000000                     16.0\n",
       "Yuefeng Song                 88.000000                      0.0\n",
       "Zach Braff                  104.000000                      0.0\n",
       "Zach Cregger                 90.000000                    138.0\n",
       "Zack Snyder                 138.375000                      0.0\n",
       "Zack Ward                    92.000000                    662.0\n",
       "Zackary Adler               110.000000                      0.0\n",
       "Zak Penn                     94.000000                     87.0\n",
       "Zal Batmanglij              100.500000                    258.0\n",
       "Zoran Lisinac               108.000000                      0.0\n",
       "Álex de la Iglesia          104.000000                    275.0\n",
       "Émile Gaudreault             92.000000                      9.0\n",
       "Éric Tessier                 99.000000                      0.0\n",
       "Étienne Faure                98.000000                     77.0\n",
       "\n",
       "[2398 rows x 2 columns]"
      ]
     },
     "execution_count": 144,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#不同列应用不同统计量\n",
    "grouped.agg({\"duration\":np.mean,\"director_facebook_likes\":np.sum})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Transformation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "df1 = df.fillna(0)\n",
    "grouped = df1.groupby(\"director_name\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "z_score = lambda s : (s-s.mean())/ s.std()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(5043, 28)"
      ]
     },
     "execution_count": 164,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df1.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>duration</th>\n",
       "      <th>director_facebook_likes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2.097852</td>\n",
       "      <td>0.748538</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.170655</td>\n",
       "      <td>1.365840</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.767547</td>\n",
       "      <td>1.253893</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.332156</td>\n",
       "      <td>1.131961</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.804768</td>\n",
       "      <td>1.153113</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.627445</td>\n",
       "      <td>1.240554</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.272360</td>\n",
       "      <td>-0.397716</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>1.192129</td>\n",
       "      <td>1.180392</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.234419</td>\n",
       "      <td>1.103096</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.817012</td>\n",
       "      <td>1.694829</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.758002</td>\n",
       "      <td>-0.443265</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.267992</td>\n",
       "      <td>0.642748</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>1.480275</td>\n",
       "      <td>0.602577</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1.551275</td>\n",
       "      <td>0.114326</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.633795</td>\n",
       "      <td>1.094827</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.604566</td>\n",
       "      <td>0.814371</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1.603245</td>\n",
       "      <td>0.657082</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2.081117</td>\n",
       "      <td>0.796995</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.313788</td>\n",
       "      <td>-0.220047</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.917738</td>\n",
       "      <td>0.746612</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.294986</td>\n",
       "      <td>0.597693</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.941364</td>\n",
       "      <td>0.506109</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.774671</td>\n",
       "      <td>0.439237</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.486912</td>\n",
       "      <td>1.001215</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.215519</td>\n",
       "      <td>1.315000</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.741201</td>\n",
       "      <td>0.997081</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>1.179993</td>\n",
       "      <td>1.604351</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.707107</td>\n",
       "      <td>0.707107</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5013</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5014</th>\n",
       "      <td>-0.720030</td>\n",
       "      <td>-0.699033</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5015</th>\n",
       "      <td>-1.076430</td>\n",
       "      <td>-0.419750</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5016</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5017</th>\n",
       "      <td>-0.707107</td>\n",
       "      <td>0.707107</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5018</th>\n",
       "      <td>-1.341426</td>\n",
       "      <td>-0.067420</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5019</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5020</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5021</th>\n",
       "      <td>-1.090906</td>\n",
       "      <td>-0.208683</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5022</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5023</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5024</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5025</th>\n",
       "      <td>0.070046</td>\n",
       "      <td>1.069309</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5026</th>\n",
       "      <td>-0.707107</td>\n",
       "      <td>-0.707107</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5027</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5028</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5029</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5030</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5031</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5032</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5033</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5034</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5035</th>\n",
       "      <td>-1.157046</td>\n",
       "      <td>-0.800032</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5036</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5037</th>\n",
       "      <td>-0.611629</td>\n",
       "      <td>-0.842927</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5038</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5039</th>\n",
       "      <td>0.829842</td>\n",
       "      <td>-0.261971</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5040</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5041</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5042</th>\n",
       "      <td>1.147079</td>\n",
       "      <td>-1.021466</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>5043 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      num_critic_for_reviews  duration  director_facebook_likes\n",
       "0                   2.097852  0.748538                      NaN\n",
       "1                   0.170655  1.365840                      NaN\n",
       "2                   0.767547  1.253893                      NaN\n",
       "3                   1.332156  1.131961                      NaN\n",
       "4                        NaN       NaN                      NaN\n",
       "5                   0.804768  1.153113                      NaN\n",
       "6                   0.627445  1.240554                      NaN\n",
       "7                        NaN       NaN                      NaN\n",
       "8                   0.272360 -0.397716                      NaN\n",
       "9                   1.192129  1.180392                      NaN\n",
       "10                  1.234419  1.103096                      NaN\n",
       "11                  0.817012  1.694829                      NaN\n",
       "12                  0.758002 -0.443265                      NaN\n",
       "13                  0.267992  0.642748                      NaN\n",
       "14                  1.480275  0.602577                      NaN\n",
       "15                  1.551275  0.114326                      NaN\n",
       "16                  0.633795  1.094827                      NaN\n",
       "17                  0.604566  0.814371                      NaN\n",
       "18                  1.603245  0.657082                      NaN\n",
       "19                  2.081117  0.796995                      NaN\n",
       "20                  0.313788 -0.220047                      NaN\n",
       "21                  0.917738  0.746612                      NaN\n",
       "22                  0.294986  0.597693                      NaN\n",
       "23                  0.941364  0.506109                      NaN\n",
       "24                  0.774671  0.439237                      NaN\n",
       "25                  0.486912  1.001215                      NaN\n",
       "26                  0.215519  1.315000                      NaN\n",
       "27                  0.741201  0.997081                      NaN\n",
       "28                  1.179993  1.604351                      NaN\n",
       "29                  0.707107  0.707107                      NaN\n",
       "...                      ...       ...                      ...\n",
       "5013                     NaN       NaN                      NaN\n",
       "5014               -0.720030 -0.699033                      NaN\n",
       "5015               -1.076430 -0.419750                      NaN\n",
       "5016                     NaN       NaN                      NaN\n",
       "5017               -0.707107  0.707107                      NaN\n",
       "5018               -1.341426 -0.067420                      NaN\n",
       "5019                     NaN       NaN                      NaN\n",
       "5020                     NaN       NaN                      NaN\n",
       "5021               -1.090906 -0.208683                      NaN\n",
       "5022                     NaN       NaN                      NaN\n",
       "5023                     NaN       NaN                      NaN\n",
       "5024                     NaN       NaN                      NaN\n",
       "5025                0.070046  1.069309                      NaN\n",
       "5026               -0.707107 -0.707107                      NaN\n",
       "5027                     NaN       NaN                      NaN\n",
       "5028                     NaN       NaN                      NaN\n",
       "5029                     NaN       NaN                      NaN\n",
       "5030                     NaN       NaN                      NaN\n",
       "5031                     NaN       NaN                      NaN\n",
       "5032                     NaN       NaN                      NaN\n",
       "5033                     NaN       NaN                      NaN\n",
       "5034                     NaN       NaN                      NaN\n",
       "5035               -1.157046 -0.800032                      NaN\n",
       "5036                     NaN       NaN                      NaN\n",
       "5037               -0.611629 -0.842927                      NaN\n",
       "5038                     NaN       NaN                      NaN\n",
       "5039                0.829842 -0.261971                      NaN\n",
       "5040                     NaN       NaN                      NaN\n",
       "5041                     NaN       NaN                      NaN\n",
       "5042                1.147079 -1.021466                      NaN\n",
       "\n",
       "[5043 rows x 3 columns]"
      ]
     },
     "execution_count": 165,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped[['num_critic_for_reviews','duration','director_facebook_likes']].transform(z_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Filteration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 172,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>color</th>\n",
       "      <th>director_name</th>\n",
       "      <th>num_critic_for_reviews</th>\n",
       "      <th>duration</th>\n",
       "      <th>director_facebook_likes</th>\n",
       "      <th>actor_3_facebook_likes</th>\n",
       "      <th>actor_2_name</th>\n",
       "      <th>actor_1_facebook_likes</th>\n",
       "      <th>gross</th>\n",
       "      <th>genres</th>\n",
       "      <th>...</th>\n",
       "      <th>num_user_for_reviews</th>\n",
       "      <th>language</th>\n",
       "      <th>country</th>\n",
       "      <th>content_rating</th>\n",
       "      <th>budget</th>\n",
       "      <th>title_year</th>\n",
       "      <th>actor_2_facebook_likes</th>\n",
       "      <th>imdb_score</th>\n",
       "      <th>aspect_ratio</th>\n",
       "      <th>movie_facebook_likes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Color</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>723.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>855.0</td>\n",
       "      <td>Joel David Moore</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>760505847.0</td>\n",
       "      <td>Action|Adventure|Fantasy|Sci-Fi</td>\n",
       "      <td>...</td>\n",
       "      <td>3054.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>237000000.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>7.9</td>\n",
       "      <td>1.78</td>\n",
       "      <td>33000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Color</td>\n",
       "      <td>Joss Whedon</td>\n",
       "      <td>635.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19000.0</td>\n",
       "      <td>Robert Downey Jr.</td>\n",
       "      <td>26000.0</td>\n",
       "      <td>458991599.0</td>\n",
       "      <td>Action|Adventure|Sci-Fi</td>\n",
       "      <td>...</td>\n",
       "      <td>1117.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>250000000.0</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>7.5</td>\n",
       "      <td>2.35</td>\n",
       "      <td>118000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Color</td>\n",
       "      <td>Joss Whedon</td>\n",
       "      <td>703.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19000.0</td>\n",
       "      <td>Robert Downey Jr.</td>\n",
       "      <td>26000.0</td>\n",
       "      <td>623279547.0</td>\n",
       "      <td>Action|Adventure|Sci-Fi</td>\n",
       "      <td>...</td>\n",
       "      <td>1722.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>220000000.0</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>8.1</td>\n",
       "      <td>1.85</td>\n",
       "      <td>123000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Color</td>\n",
       "      <td>Peter Jackson</td>\n",
       "      <td>422.0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>773.0</td>\n",
       "      <td>Adam Brown</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>255108370.0</td>\n",
       "      <td>Adventure|Fantasy</td>\n",
       "      <td>...</td>\n",
       "      <td>802.0</td>\n",
       "      <td>English</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>250000000.0</td>\n",
       "      <td>2014.0</td>\n",
       "      <td>972.0</td>\n",
       "      <td>7.5</td>\n",
       "      <td>2.35</td>\n",
       "      <td>65000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Color</td>\n",
       "      <td>Peter Jackson</td>\n",
       "      <td>509.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>773.0</td>\n",
       "      <td>Adam Brown</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>258355354.0</td>\n",
       "      <td>Adventure|Fantasy</td>\n",
       "      <td>...</td>\n",
       "      <td>951.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>225000000.0</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>972.0</td>\n",
       "      <td>7.9</td>\n",
       "      <td>2.35</td>\n",
       "      <td>83000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Color</td>\n",
       "      <td>Peter Jackson</td>\n",
       "      <td>446.0</td>\n",
       "      <td>201.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>Thomas Kretschmann</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>218051260.0</td>\n",
       "      <td>Action|Adventure|Drama|Romance</td>\n",
       "      <td>...</td>\n",
       "      <td>2618.0</td>\n",
       "      <td>English</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>207000000.0</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>919.0</td>\n",
       "      <td>7.2</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Color</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>315.0</td>\n",
       "      <td>194.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>794.0</td>\n",
       "      <td>Kate Winslet</td>\n",
       "      <td>29000.0</td>\n",
       "      <td>658672302.0</td>\n",
       "      <td>Drama|Romance</td>\n",
       "      <td>...</td>\n",
       "      <td>2528.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>200000000.0</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>7.7</td>\n",
       "      <td>2.35</td>\n",
       "      <td>26000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>Color</td>\n",
       "      <td>Peter Jackson</td>\n",
       "      <td>645.0</td>\n",
       "      <td>182.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>773.0</td>\n",
       "      <td>Adam Brown</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>303001229.0</td>\n",
       "      <td>Adventure|Fantasy</td>\n",
       "      <td>...</td>\n",
       "      <td>1367.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>180000000.0</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>972.0</td>\n",
       "      <td>7.9</td>\n",
       "      <td>2.35</td>\n",
       "      <td>166000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>Color</td>\n",
       "      <td>Wolfgang Petersen</td>\n",
       "      <td>231.0</td>\n",
       "      <td>98.0</td>\n",
       "      <td>249.0</td>\n",
       "      <td>702.0</td>\n",
       "      <td>Mike Vogel</td>\n",
       "      <td>87000.0</td>\n",
       "      <td>60655503.0</td>\n",
       "      <td>Action|Adventure|Drama|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>629.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>160000000.0</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>5.6</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>Color</td>\n",
       "      <td>Wolfgang Petersen</td>\n",
       "      <td>220.0</td>\n",
       "      <td>196.0</td>\n",
       "      <td>249.0</td>\n",
       "      <td>844.0</td>\n",
       "      <td>Orlando Bloom</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>133228348.0</td>\n",
       "      <td>Adventure</td>\n",
       "      <td>...</td>\n",
       "      <td>1694.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>175000000.0</td>\n",
       "      <td>2004.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>7.2</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>Color</td>\n",
       "      <td>Wolfgang Petersen</td>\n",
       "      <td>231.0</td>\n",
       "      <td>130.0</td>\n",
       "      <td>249.0</td>\n",
       "      <td>461.0</td>\n",
       "      <td>Mary Elizabeth Mastrantonio</td>\n",
       "      <td>784.0</td>\n",
       "      <td>182618434.0</td>\n",
       "      <td>Action|Adventure|Drama|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>779.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>140000000.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>638.0</td>\n",
       "      <td>6.4</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>270</th>\n",
       "      <td>Color</td>\n",
       "      <td>Peter Jackson</td>\n",
       "      <td>297.0</td>\n",
       "      <td>171.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>857.0</td>\n",
       "      <td>Orlando Bloom</td>\n",
       "      <td>16000.0</td>\n",
       "      <td>313837577.0</td>\n",
       "      <td>Action|Adventure|Drama|Fantasy</td>\n",
       "      <td>...</td>\n",
       "      <td>5060.0</td>\n",
       "      <td>English</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>93000000.0</td>\n",
       "      <td>2001.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>8.8</td>\n",
       "      <td>2.35</td>\n",
       "      <td>21000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>288</th>\n",
       "      <td>Color</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>210.0</td>\n",
       "      <td>153.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>539.0</td>\n",
       "      <td>Jenette Goldstein</td>\n",
       "      <td>780.0</td>\n",
       "      <td>204843350.0</td>\n",
       "      <td>Action|Sci-Fi</td>\n",
       "      <td>...</td>\n",
       "      <td>983.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>102000000.0</td>\n",
       "      <td>1991.0</td>\n",
       "      <td>604.0</td>\n",
       "      <td>8.5</td>\n",
       "      <td>2.35</td>\n",
       "      <td>13000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>291</th>\n",
       "      <td>Color</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>94.0</td>\n",
       "      <td>141.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>618.0</td>\n",
       "      <td>Tia Carrere</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>146282411.0</td>\n",
       "      <td>Action|Comedy|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>351.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>115000000.0</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>7.2</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>337</th>\n",
       "      <td>Color</td>\n",
       "      <td>Peter Jackson</td>\n",
       "      <td>308.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>310.0</td>\n",
       "      <td>AJ Michalka</td>\n",
       "      <td>873.0</td>\n",
       "      <td>43982842.0</td>\n",
       "      <td>Drama|Fantasy|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>593.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>65000000.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>560.0</td>\n",
       "      <td>6.7</td>\n",
       "      <td>2.35</td>\n",
       "      <td>16000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>339</th>\n",
       "      <td>Color</td>\n",
       "      <td>Peter Jackson</td>\n",
       "      <td>328.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>416.0</td>\n",
       "      <td>Billy Boyd</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>377019252.0</td>\n",
       "      <td>Action|Adventure|Drama|Fantasy</td>\n",
       "      <td>...</td>\n",
       "      <td>3189.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>94000000.0</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>857.0</td>\n",
       "      <td>8.9</td>\n",
       "      <td>2.35</td>\n",
       "      <td>16000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>340</th>\n",
       "      <td>Color</td>\n",
       "      <td>Peter Jackson</td>\n",
       "      <td>294.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>857.0</td>\n",
       "      <td>Orlando Bloom</td>\n",
       "      <td>16000.0</td>\n",
       "      <td>340478898.0</td>\n",
       "      <td>Action|Adventure|Drama|Fantasy</td>\n",
       "      <td>...</td>\n",
       "      <td>2417.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>94000000.0</td>\n",
       "      <td>2002.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>8.7</td>\n",
       "      <td>2.35</td>\n",
       "      <td>10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>399</th>\n",
       "      <td>Color</td>\n",
       "      <td>Wolfgang Petersen</td>\n",
       "      <td>142.0</td>\n",
       "      <td>124.0</td>\n",
       "      <td>249.0</td>\n",
       "      <td>936.0</td>\n",
       "      <td>Gary Oldman</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>172620724.0</td>\n",
       "      <td>Action|Adventure|Drama|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>393.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>85000000.0</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>10000.0</td>\n",
       "      <td>6.4</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>462</th>\n",
       "      <td>Color</td>\n",
       "      <td>Anthony Minghella</td>\n",
       "      <td>198.0</td>\n",
       "      <td>154.0</td>\n",
       "      <td>333.0</td>\n",
       "      <td>16000.0</td>\n",
       "      <td>Natalie Portman</td>\n",
       "      <td>22000.0</td>\n",
       "      <td>95632614.0</td>\n",
       "      <td>Adventure|Drama|History|Romance|War</td>\n",
       "      <td>...</td>\n",
       "      <td>674.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>79000000.0</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>20000.0</td>\n",
       "      <td>7.2</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>Color</td>\n",
       "      <td>Kevin Costner</td>\n",
       "      <td>79.0</td>\n",
       "      <td>177.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>582.0</td>\n",
       "      <td>Brian Anthony Wilson</td>\n",
       "      <td>766.0</td>\n",
       "      <td>17593391.0</td>\n",
       "      <td>Action|Adventure|Drama|Sci-Fi</td>\n",
       "      <td>...</td>\n",
       "      <td>376.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>80000000.0</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>674.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>576</th>\n",
       "      <td>Color</td>\n",
       "      <td>Frank Darabont</td>\n",
       "      <td>128.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>745.0</td>\n",
       "      <td>Hal Holbrook</td>\n",
       "      <td>940.0</td>\n",
       "      <td>27796042.0</td>\n",
       "      <td>Drama|Romance</td>\n",
       "      <td>...</td>\n",
       "      <td>376.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG</td>\n",
       "      <td>72000000.0</td>\n",
       "      <td>2001.0</td>\n",
       "      <td>826.0</td>\n",
       "      <td>6.9</td>\n",
       "      <td>1.85</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>606</th>\n",
       "      <td>Color</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>82.0</td>\n",
       "      <td>171.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>638.0</td>\n",
       "      <td>Todd Graff</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>54222000.0</td>\n",
       "      <td>Adventure|Drama|Sci-Fi|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>380.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>69500000.0</td>\n",
       "      <td>1989.0</td>\n",
       "      <td>650.0</td>\n",
       "      <td>7.6</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>681</th>\n",
       "      <td>Color</td>\n",
       "      <td>Taylor Hackford</td>\n",
       "      <td>134.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>184.0</td>\n",
       "      <td>Alun Armstrong</td>\n",
       "      <td>324.0</td>\n",
       "      <td>32598931.0</td>\n",
       "      <td>Action|Drama|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>265.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>65000000.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>192.0</td>\n",
       "      <td>6.2</td>\n",
       "      <td>2.35</td>\n",
       "      <td>892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>712</th>\n",
       "      <td>Color</td>\n",
       "      <td>Frank Darabont</td>\n",
       "      <td>186.0</td>\n",
       "      <td>189.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>693.0</td>\n",
       "      <td>Jeffrey DeMunn</td>\n",
       "      <td>15000.0</td>\n",
       "      <td>136801374.0</td>\n",
       "      <td>Crime|Drama|Fantasy|Mystery</td>\n",
       "      <td>...</td>\n",
       "      <td>1377.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>60000000.0</td>\n",
       "      <td>1999.0</td>\n",
       "      <td>745.0</td>\n",
       "      <td>8.5</td>\n",
       "      <td>1.85</td>\n",
       "      <td>30000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>794</th>\n",
       "      <td>Color</td>\n",
       "      <td>Joss Whedon</td>\n",
       "      <td>703.0</td>\n",
       "      <td>173.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19000.0</td>\n",
       "      <td>Robert Downey Jr.</td>\n",
       "      <td>26000.0</td>\n",
       "      <td>623279547.0</td>\n",
       "      <td>Action|Adventure|Sci-Fi</td>\n",
       "      <td>...</td>\n",
       "      <td>1722.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>220000000.0</td>\n",
       "      <td>2012.0</td>\n",
       "      <td>21000.0</td>\n",
       "      <td>8.1</td>\n",
       "      <td>1.85</td>\n",
       "      <td>123000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>827</th>\n",
       "      <td>Color</td>\n",
       "      <td>Taylor Hackford</td>\n",
       "      <td>117.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>138.0</td>\n",
       "      <td>9000.0</td>\n",
       "      <td>Al Pacino</td>\n",
       "      <td>18000.0</td>\n",
       "      <td>60984028.0</td>\n",
       "      <td>Drama|Mystery|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>431.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>57000000.0</td>\n",
       "      <td>1997.0</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>7.5</td>\n",
       "      <td>2.35</td>\n",
       "      <td>11000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>883</th>\n",
       "      <td>Color</td>\n",
       "      <td>Ron Maxwell</td>\n",
       "      <td>84.0</td>\n",
       "      <td>280.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>Bruce Boxleitner</td>\n",
       "      <td>789.0</td>\n",
       "      <td>12870569.0</td>\n",
       "      <td>Drama|History|War</td>\n",
       "      <td>...</td>\n",
       "      <td>497.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>56000000.0</td>\n",
       "      <td>2003.0</td>\n",
       "      <td>640.0</td>\n",
       "      <td>6.3</td>\n",
       "      <td>2.35</td>\n",
       "      <td>953</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>895</th>\n",
       "      <td>Color</td>\n",
       "      <td>Francis Ford Coppola</td>\n",
       "      <td>110.0</td>\n",
       "      <td>170.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>889.0</td>\n",
       "      <td>Joe Mantegna</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>66676062.0</td>\n",
       "      <td>Crime|Drama</td>\n",
       "      <td>...</td>\n",
       "      <td>545.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>54000000.0</td>\n",
       "      <td>1990.0</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>7.6</td>\n",
       "      <td>1.85</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>957</th>\n",
       "      <td>Color</td>\n",
       "      <td>Wolfgang Petersen</td>\n",
       "      <td>64.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>249.0</td>\n",
       "      <td>808.0</td>\n",
       "      <td>Morgan Freeman</td>\n",
       "      <td>18000.0</td>\n",
       "      <td>67823573.0</td>\n",
       "      <td>Action|Drama|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>130.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>50000000.0</td>\n",
       "      <td>1995.0</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>6.6</td>\n",
       "      <td>1.85</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1051</th>\n",
       "      <td>Color</td>\n",
       "      <td>Francis Ford Coppola</td>\n",
       "      <td>36.0</td>\n",
       "      <td>123.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>886.0</td>\n",
       "      <td>Bob Hoskins</td>\n",
       "      <td>12000.0</td>\n",
       "      <td>25900000.0</td>\n",
       "      <td>Crime|Drama|Music</td>\n",
       "      <td>...</td>\n",
       "      <td>84.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>58000000.0</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>5000.0</td>\n",
       "      <td>6.5</td>\n",
       "      <td>1.85</td>\n",
       "      <td>828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3537</th>\n",
       "      <td>Color</td>\n",
       "      <td>Francis Ford Coppola</td>\n",
       "      <td>112.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>507.0</td>\n",
       "      <td>Bruce Dern</td>\n",
       "      <td>1000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Comedy|Fantasy|Horror|Mystery</td>\n",
       "      <td>...</td>\n",
       "      <td>70.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>7000000.0</td>\n",
       "      <td>2011.0</td>\n",
       "      <td>844.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>1.85</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3575</th>\n",
       "      <td>Color</td>\n",
       "      <td>James Cameron</td>\n",
       "      <td>204.0</td>\n",
       "      <td>107.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>255.0</td>\n",
       "      <td>Brian Thompson</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>38400000.0</td>\n",
       "      <td>Action|Sci-Fi</td>\n",
       "      <td>...</td>\n",
       "      <td>692.0</td>\n",
       "      <td>English</td>\n",
       "      <td>UK</td>\n",
       "      <td>R</td>\n",
       "      <td>6500000.0</td>\n",
       "      <td>1984.0</td>\n",
       "      <td>663.0</td>\n",
       "      <td>8.1</td>\n",
       "      <td>1.85</td>\n",
       "      <td>13000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3588</th>\n",
       "      <td>Color</td>\n",
       "      <td>Jerome Robbins</td>\n",
       "      <td>120.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>249.0</td>\n",
       "      <td>George Chakiris</td>\n",
       "      <td>804.0</td>\n",
       "      <td>43650000.0</td>\n",
       "      <td>Crime|Drama|Musical|Romance|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>316.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>Unrated</td>\n",
       "      <td>6000000.0</td>\n",
       "      <td>1961.0</td>\n",
       "      <td>271.0</td>\n",
       "      <td>7.6</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3685</th>\n",
       "      <td>Color</td>\n",
       "      <td>Rakeysh Omprakash Mehra</td>\n",
       "      <td>33.0</td>\n",
       "      <td>157.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>199.0</td>\n",
       "      <td>Steven Mackintosh</td>\n",
       "      <td>397.0</td>\n",
       "      <td>2197331.0</td>\n",
       "      <td>Comedy|Drama|History|Romance</td>\n",
       "      <td>...</td>\n",
       "      <td>321.0</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>India</td>\n",
       "      <td>Not Rated</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2006.0</td>\n",
       "      <td>227.0</td>\n",
       "      <td>8.4</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3763</th>\n",
       "      <td>Color</td>\n",
       "      <td>Jay Levey</td>\n",
       "      <td>59.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>448.0</td>\n",
       "      <td>Gedde Watanabe</td>\n",
       "      <td>859.0</td>\n",
       "      <td>6157157.0</td>\n",
       "      <td>Comedy|Drama</td>\n",
       "      <td>...</td>\n",
       "      <td>198.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>5000000.0</td>\n",
       "      <td>1989.0</td>\n",
       "      <td>448.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.85</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3766</th>\n",
       "      <td>Color</td>\n",
       "      <td>Sergio Leone</td>\n",
       "      <td>164.0</td>\n",
       "      <td>145.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>392.0</td>\n",
       "      <td>Woody Strode</td>\n",
       "      <td>973.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Western</td>\n",
       "      <td>...</td>\n",
       "      <td>565.0</td>\n",
       "      <td>English</td>\n",
       "      <td>Italy</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>5000000.0</td>\n",
       "      <td>1968.0</td>\n",
       "      <td>423.0</td>\n",
       "      <td>8.6</td>\n",
       "      <td>2.35</td>\n",
       "      <td>10000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3775</th>\n",
       "      <td>Color</td>\n",
       "      <td>Peter Jackson</td>\n",
       "      <td>93.0</td>\n",
       "      <td>108.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>88.0</td>\n",
       "      <td>Jed Brophy</td>\n",
       "      <td>14000.0</td>\n",
       "      <td>3049135.0</td>\n",
       "      <td>Biography|Crime|Drama|Romance|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>265.0</td>\n",
       "      <td>English</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>R</td>\n",
       "      <td>5000000.0</td>\n",
       "      <td>1994.0</td>\n",
       "      <td>433.0</td>\n",
       "      <td>7.4</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3821</th>\n",
       "      <td>Color</td>\n",
       "      <td>Billy Bob Thornton</td>\n",
       "      <td>104.0</td>\n",
       "      <td>148.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>263.0</td>\n",
       "      <td>Dwight Yoakam</td>\n",
       "      <td>3000.0</td>\n",
       "      <td>24475416.0</td>\n",
       "      <td>Drama</td>\n",
       "      <td>...</td>\n",
       "      <td>309.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>890000.0</td>\n",
       "      <td>1996.0</td>\n",
       "      <td>324.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.85</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3890</th>\n",
       "      <td>Color</td>\n",
       "      <td>Cecil B. DeMille</td>\n",
       "      <td>44.0</td>\n",
       "      <td>152.0</td>\n",
       "      <td>309.0</td>\n",
       "      <td>132.0</td>\n",
       "      <td>Dorothy Lamour</td>\n",
       "      <td>232.0</td>\n",
       "      <td>36000000.0</td>\n",
       "      <td>Drama|Family|Romance</td>\n",
       "      <td>...</td>\n",
       "      <td>107.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>Not Rated</td>\n",
       "      <td>4000000.0</td>\n",
       "      <td>1952.0</td>\n",
       "      <td>178.0</td>\n",
       "      <td>6.7</td>\n",
       "      <td>1.37</td>\n",
       "      <td>625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3903</th>\n",
       "      <td>Color</td>\n",
       "      <td>John Sturges</td>\n",
       "      <td>111.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>120.0</td>\n",
       "      <td>145.0</td>\n",
       "      <td>Donald Pleasence</td>\n",
       "      <td>773.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Adventure|Drama|History|Thriller|War</td>\n",
       "      <td>...</td>\n",
       "      <td>301.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>Approved</td>\n",
       "      <td>4000000.0</td>\n",
       "      <td>1963.0</td>\n",
       "      <td>742.0</td>\n",
       "      <td>8.3</td>\n",
       "      <td>2.35</td>\n",
       "      <td>8000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3958</th>\n",
       "      <td>Color</td>\n",
       "      <td>Peter H. Hunt</td>\n",
       "      <td>34.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>69.0</td>\n",
       "      <td>Ken Howard</td>\n",
       "      <td>713.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Drama|Family|History|Musical</td>\n",
       "      <td>...</td>\n",
       "      <td>129.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG</td>\n",
       "      <td>4000000.0</td>\n",
       "      <td>1972.0</td>\n",
       "      <td>649.0</td>\n",
       "      <td>7.6</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3970</th>\n",
       "      <td>Color</td>\n",
       "      <td>Victor Fleming</td>\n",
       "      <td>157.0</td>\n",
       "      <td>226.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>248.0</td>\n",
       "      <td>George Reeves</td>\n",
       "      <td>503.0</td>\n",
       "      <td>198655278.0</td>\n",
       "      <td>Drama|History|Romance|War</td>\n",
       "      <td>...</td>\n",
       "      <td>706.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>G</td>\n",
       "      <td>3977000.0</td>\n",
       "      <td>1939.0</td>\n",
       "      <td>384.0</td>\n",
       "      <td>8.2</td>\n",
       "      <td>1.37</td>\n",
       "      <td>16000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4066</th>\n",
       "      <td>Color</td>\n",
       "      <td>David Lean</td>\n",
       "      <td>122.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>767.0</td>\n",
       "      <td>87.0</td>\n",
       "      <td>Sessue Hayakawa</td>\n",
       "      <td>682.0</td>\n",
       "      <td>27200000.0</td>\n",
       "      <td>Adventure|Drama|War</td>\n",
       "      <td>...</td>\n",
       "      <td>273.0</td>\n",
       "      <td>English</td>\n",
       "      <td>UK</td>\n",
       "      <td>PG</td>\n",
       "      <td>3000000.0</td>\n",
       "      <td>1957.0</td>\n",
       "      <td>119.0</td>\n",
       "      <td>8.2</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4077</th>\n",
       "      <td>Black and White</td>\n",
       "      <td>Stanley Kramer</td>\n",
       "      <td>73.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>176.0</td>\n",
       "      <td>760.0</td>\n",
       "      <td>Montgomery Clift</td>\n",
       "      <td>877.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Drama|War</td>\n",
       "      <td>...</td>\n",
       "      <td>176.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>Not Rated</td>\n",
       "      <td>3000000.0</td>\n",
       "      <td>1961.0</td>\n",
       "      <td>862.0</td>\n",
       "      <td>8.3</td>\n",
       "      <td>1.75</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4157</th>\n",
       "      <td>Black and White</td>\n",
       "      <td>Victor Fleming</td>\n",
       "      <td>213.0</td>\n",
       "      <td>102.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>357.0</td>\n",
       "      <td>Terry</td>\n",
       "      <td>695.0</td>\n",
       "      <td>22202612.0</td>\n",
       "      <td>Adventure|Family|Fantasy|Musical</td>\n",
       "      <td>...</td>\n",
       "      <td>533.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>Passed</td>\n",
       "      <td>2800000.0</td>\n",
       "      <td>1939.0</td>\n",
       "      <td>421.0</td>\n",
       "      <td>8.1</td>\n",
       "      <td>1.37</td>\n",
       "      <td>14000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4167</th>\n",
       "      <td>Black and White</td>\n",
       "      <td>Victor Fleming</td>\n",
       "      <td>9.0</td>\n",
       "      <td>122.0</td>\n",
       "      <td>149.0</td>\n",
       "      <td>315.0</td>\n",
       "      <td>Esther Williams</td>\n",
       "      <td>760.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Drama|Fantasy|Romance|War</td>\n",
       "      <td>...</td>\n",
       "      <td>27.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>Passed</td>\n",
       "      <td>2627000.0</td>\n",
       "      <td>1943.0</td>\n",
       "      <td>675.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.37</td>\n",
       "      <td>116</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4238</th>\n",
       "      <td>Black and White</td>\n",
       "      <td>William Wyler</td>\n",
       "      <td>97.0</td>\n",
       "      <td>172.0</td>\n",
       "      <td>355.0</td>\n",
       "      <td>188.0</td>\n",
       "      <td>Teresa Wright</td>\n",
       "      <td>749.0</td>\n",
       "      <td>23650000.0</td>\n",
       "      <td>Drama|Romance|War</td>\n",
       "      <td>...</td>\n",
       "      <td>235.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>Not Rated</td>\n",
       "      <td>2100000.0</td>\n",
       "      <td>1946.0</td>\n",
       "      <td>208.0</td>\n",
       "      <td>8.1</td>\n",
       "      <td>1.37</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4351</th>\n",
       "      <td>Color</td>\n",
       "      <td>Remo</td>\n",
       "      <td>15.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>Remo</td>\n",
       "      <td>733.0</td>\n",
       "      <td>95236.0</td>\n",
       "      <td>Drama|Musical</td>\n",
       "      <td>...</td>\n",
       "      <td>38.0</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>India</td>\n",
       "      <td>Not Rated</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2013.0</td>\n",
       "      <td>168.0</td>\n",
       "      <td>6.4</td>\n",
       "      <td>0.00</td>\n",
       "      <td>1000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4365</th>\n",
       "      <td>Color</td>\n",
       "      <td>Vijay Chandar</td>\n",
       "      <td>3.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>T.R. Silambarasan</td>\n",
       "      <td>141.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Comedy|Romance</td>\n",
       "      <td>...</td>\n",
       "      <td>6.0</td>\n",
       "      <td>Tamil</td>\n",
       "      <td>India</td>\n",
       "      <td>0</td>\n",
       "      <td>150000000.0</td>\n",
       "      <td>2015.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>5.1</td>\n",
       "      <td>0.00</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4396</th>\n",
       "      <td>Color</td>\n",
       "      <td>Francis Ford Coppola</td>\n",
       "      <td>149.0</td>\n",
       "      <td>113.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>324.0</td>\n",
       "      <td>Teri Garr</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Drama|Mystery|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>313.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG</td>\n",
       "      <td>1600000.0</td>\n",
       "      <td>1974.0</td>\n",
       "      <td>481.0</td>\n",
       "      <td>7.9</td>\n",
       "      <td>1.37</td>\n",
       "      <td>6000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4498</th>\n",
       "      <td>Color</td>\n",
       "      <td>Sergio Leone</td>\n",
       "      <td>181.0</td>\n",
       "      <td>142.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>Luigi Pistilli</td>\n",
       "      <td>16000.0</td>\n",
       "      <td>6100000.0</td>\n",
       "      <td>Western</td>\n",
       "      <td>...</td>\n",
       "      <td>780.0</td>\n",
       "      <td>Italian</td>\n",
       "      <td>Italy</td>\n",
       "      <td>Approved</td>\n",
       "      <td>1200000.0</td>\n",
       "      <td>1966.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>8.9</td>\n",
       "      <td>2.35</td>\n",
       "      <td>20000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4528</th>\n",
       "      <td>Color</td>\n",
       "      <td>Shimit Amin</td>\n",
       "      <td>14.0</td>\n",
       "      <td>150.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>Shazahn Padamsee</td>\n",
       "      <td>964.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Comedy|Drama</td>\n",
       "      <td>...</td>\n",
       "      <td>35.0</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>India</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>7.5</td>\n",
       "      <td>0.00</td>\n",
       "      <td>773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4572</th>\n",
       "      <td>Black and White</td>\n",
       "      <td>Khalid Mohamed</td>\n",
       "      <td>1.0</td>\n",
       "      <td>167.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>97.0</td>\n",
       "      <td>Manoj Bajpayee</td>\n",
       "      <td>353.0</td>\n",
       "      <td>610991.0</td>\n",
       "      <td>Drama|Romance</td>\n",
       "      <td>...</td>\n",
       "      <td>19.0</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>India</td>\n",
       "      <td>0</td>\n",
       "      <td>1000000.0</td>\n",
       "      <td>2000.0</td>\n",
       "      <td>186.0</td>\n",
       "      <td>6.2</td>\n",
       "      <td>2.35</td>\n",
       "      <td>92</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4584</th>\n",
       "      <td>Color</td>\n",
       "      <td>Peter Jackson</td>\n",
       "      <td>308.0</td>\n",
       "      <td>135.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>310.0</td>\n",
       "      <td>AJ Michalka</td>\n",
       "      <td>873.0</td>\n",
       "      <td>43982842.0</td>\n",
       "      <td>Drama|Fantasy|Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>593.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>65000000.0</td>\n",
       "      <td>2009.0</td>\n",
       "      <td>559.0</td>\n",
       "      <td>6.7</td>\n",
       "      <td>2.35</td>\n",
       "      <td>16000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4593</th>\n",
       "      <td>Color</td>\n",
       "      <td>Vivek Agnihotri</td>\n",
       "      <td>4.0</td>\n",
       "      <td>160.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>219.0</td>\n",
       "      <td>Anil Kapoor</td>\n",
       "      <td>724.0</td>\n",
       "      <td>49000.0</td>\n",
       "      <td>Thriller</td>\n",
       "      <td>...</td>\n",
       "      <td>30.0</td>\n",
       "      <td>Hindi</td>\n",
       "      <td>India</td>\n",
       "      <td>0</td>\n",
       "      <td>1500000.0</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>668.0</td>\n",
       "      <td>4.8</td>\n",
       "      <td>0.00</td>\n",
       "      <td>31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4682</th>\n",
       "      <td>Color</td>\n",
       "      <td>Bernardo Bertolucci</td>\n",
       "      <td>120.0</td>\n",
       "      <td>106.0</td>\n",
       "      <td>973.0</td>\n",
       "      <td>48.0</td>\n",
       "      <td>Stefania Sandrelli</td>\n",
       "      <td>319.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>Drama</td>\n",
       "      <td>...</td>\n",
       "      <td>101.0</td>\n",
       "      <td>Italian</td>\n",
       "      <td>Italy</td>\n",
       "      <td>R</td>\n",
       "      <td>750000.0</td>\n",
       "      <td>1970.0</td>\n",
       "      <td>90.0</td>\n",
       "      <td>8.1</td>\n",
       "      <td>1.66</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4694</th>\n",
       "      <td>Color</td>\n",
       "      <td>Peter Jackson</td>\n",
       "      <td>446.0</td>\n",
       "      <td>201.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>84.0</td>\n",
       "      <td>Thomas Kretschmann</td>\n",
       "      <td>6000.0</td>\n",
       "      <td>218051260.0</td>\n",
       "      <td>Action|Adventure|Drama|Romance</td>\n",
       "      <td>...</td>\n",
       "      <td>2618.0</td>\n",
       "      <td>English</td>\n",
       "      <td>New Zealand</td>\n",
       "      <td>PG-13</td>\n",
       "      <td>207000000.0</td>\n",
       "      <td>2005.0</td>\n",
       "      <td>918.0</td>\n",
       "      <td>7.2</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4708</th>\n",
       "      <td>Color</td>\n",
       "      <td>Michael Wadleigh</td>\n",
       "      <td>53.0</td>\n",
       "      <td>215.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>136.0</td>\n",
       "      <td>Jimi Hendrix</td>\n",
       "      <td>262.0</td>\n",
       "      <td>13300000.0</td>\n",
       "      <td>Documentary|History|Music</td>\n",
       "      <td>...</td>\n",
       "      <td>63.0</td>\n",
       "      <td>English</td>\n",
       "      <td>USA</td>\n",
       "      <td>R</td>\n",
       "      <td>600000.0</td>\n",
       "      <td>1970.0</td>\n",
       "      <td>227.0</td>\n",
       "      <td>8.1</td>\n",
       "      <td>2.20</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4747</th>\n",
       "      <td>Black and White</td>\n",
       "      <td>Akira Kurosawa</td>\n",
       "      <td>153.0</td>\n",
       "      <td>202.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>Minoru Chiaki</td>\n",
       "      <td>304.0</td>\n",
       "      <td>269061.0</td>\n",
       "      <td>Action|Adventure|Drama</td>\n",
       "      <td>...</td>\n",
       "      <td>596.0</td>\n",
       "      <td>Japanese</td>\n",
       "      <td>Japan</td>\n",
       "      <td>Unrated</td>\n",
       "      <td>2000000.0</td>\n",
       "      <td>1954.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>8.7</td>\n",
       "      <td>1.37</td>\n",
       "      <td>11000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4897</th>\n",
       "      <td>Color</td>\n",
       "      <td>Sergio Leone</td>\n",
       "      <td>122.0</td>\n",
       "      <td>99.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>93.0</td>\n",
       "      <td>Gian Maria Volontè</td>\n",
       "      <td>16000.0</td>\n",
       "      <td>3500000.0</td>\n",
       "      <td>Action|Drama|Western</td>\n",
       "      <td>...</td>\n",
       "      <td>235.0</td>\n",
       "      <td>Italian</td>\n",
       "      <td>Italy</td>\n",
       "      <td>R</td>\n",
       "      <td>200000.0</td>\n",
       "      <td>1964.0</td>\n",
       "      <td>360.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>2.35</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>124 rows × 28 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                 color            director_name  num_critic_for_reviews  \\\n",
       "0                Color            James Cameron                   723.0   \n",
       "8                Color              Joss Whedon                   635.0   \n",
       "17               Color              Joss Whedon                   703.0   \n",
       "20               Color            Peter Jackson                   422.0   \n",
       "23               Color            Peter Jackson                   509.0   \n",
       "25               Color            Peter Jackson                   446.0   \n",
       "26               Color            James Cameron                   315.0   \n",
       "99               Color            Peter Jackson                   645.0   \n",
       "105              Color        Wolfgang Petersen                   231.0   \n",
       "147              Color        Wolfgang Petersen                   220.0   \n",
       "221              Color        Wolfgang Petersen                   231.0   \n",
       "270              Color            Peter Jackson                   297.0   \n",
       "288              Color            James Cameron                   210.0   \n",
       "291              Color            James Cameron                    94.0   \n",
       "337              Color            Peter Jackson                   308.0   \n",
       "339              Color            Peter Jackson                   328.0   \n",
       "340              Color            Peter Jackson                   294.0   \n",
       "399              Color        Wolfgang Petersen                   142.0   \n",
       "462              Color        Anthony Minghella                   198.0   \n",
       "499              Color            Kevin Costner                    79.0   \n",
       "576              Color           Frank Darabont                   128.0   \n",
       "606              Color            James Cameron                    82.0   \n",
       "681              Color          Taylor Hackford                   134.0   \n",
       "712              Color           Frank Darabont                   186.0   \n",
       "794              Color              Joss Whedon                   703.0   \n",
       "827              Color          Taylor Hackford                   117.0   \n",
       "883              Color              Ron Maxwell                    84.0   \n",
       "895              Color     Francis Ford Coppola                   110.0   \n",
       "957              Color        Wolfgang Petersen                    64.0   \n",
       "1051             Color     Francis Ford Coppola                    36.0   \n",
       "...                ...                      ...                     ...   \n",
       "3537             Color     Francis Ford Coppola                   112.0   \n",
       "3575             Color            James Cameron                   204.0   \n",
       "3588             Color           Jerome Robbins                   120.0   \n",
       "3685             Color  Rakeysh Omprakash Mehra                    33.0   \n",
       "3763             Color                Jay Levey                    59.0   \n",
       "3766             Color             Sergio Leone                   164.0   \n",
       "3775             Color            Peter Jackson                    93.0   \n",
       "3821             Color       Billy Bob Thornton                   104.0   \n",
       "3890             Color         Cecil B. DeMille                    44.0   \n",
       "3903             Color             John Sturges                   111.0   \n",
       "3958             Color            Peter H. Hunt                    34.0   \n",
       "3970             Color           Victor Fleming                   157.0   \n",
       "4066             Color               David Lean                   122.0   \n",
       "4077   Black and White           Stanley Kramer                    73.0   \n",
       "4157   Black and White           Victor Fleming                   213.0   \n",
       "4167   Black and White           Victor Fleming                     9.0   \n",
       "4238   Black and White            William Wyler                    97.0   \n",
       "4351             Color                     Remo                    15.0   \n",
       "4365             Color            Vijay Chandar                     3.0   \n",
       "4396             Color     Francis Ford Coppola                   149.0   \n",
       "4498             Color             Sergio Leone                   181.0   \n",
       "4528             Color              Shimit Amin                    14.0   \n",
       "4572   Black and White           Khalid Mohamed                     1.0   \n",
       "4584             Color            Peter Jackson                   308.0   \n",
       "4593             Color          Vivek Agnihotri                     4.0   \n",
       "4682             Color      Bernardo Bertolucci                   120.0   \n",
       "4694             Color            Peter Jackson                   446.0   \n",
       "4708             Color         Michael Wadleigh                    53.0   \n",
       "4747   Black and White           Akira Kurosawa                   153.0   \n",
       "4897             Color             Sergio Leone                   122.0   \n",
       "\n",
       "      duration  director_facebook_likes  actor_3_facebook_likes  \\\n",
       "0        178.0                      0.0                   855.0   \n",
       "8        141.0                      0.0                 19000.0   \n",
       "17       173.0                      0.0                 19000.0   \n",
       "20       164.0                      0.0                   773.0   \n",
       "23       186.0                      0.0                   773.0   \n",
       "25       201.0                      0.0                    84.0   \n",
       "26       194.0                      0.0                   794.0   \n",
       "99       182.0                      0.0                   773.0   \n",
       "105       98.0                    249.0                   702.0   \n",
       "147      196.0                    249.0                   844.0   \n",
       "221      130.0                    249.0                   461.0   \n",
       "270      171.0                      0.0                   857.0   \n",
       "288      153.0                      0.0                   539.0   \n",
       "291      141.0                      0.0                   618.0   \n",
       "337      135.0                      0.0                   310.0   \n",
       "339      192.0                      0.0                   416.0   \n",
       "340      172.0                      0.0                   857.0   \n",
       "399      124.0                    249.0                   936.0   \n",
       "462      154.0                    333.0                 16000.0   \n",
       "499      177.0                      0.0                   582.0   \n",
       "576      152.0                      0.0                   745.0   \n",
       "606      171.0                      0.0                   638.0   \n",
       "681      135.0                    138.0                   184.0   \n",
       "712      189.0                      0.0                   693.0   \n",
       "794      173.0                      0.0                 19000.0   \n",
       "827      136.0                    138.0                  9000.0   \n",
       "883      280.0                     33.0                    67.0   \n",
       "895      170.0                      0.0                   889.0   \n",
       "957      127.0                    249.0                   808.0   \n",
       "1051     123.0                      0.0                   886.0   \n",
       "...        ...                      ...                     ...   \n",
       "3537      88.0                      0.0                   507.0   \n",
       "3575     107.0                      0.0                   255.0   \n",
       "3588     152.0                     34.0                   249.0   \n",
       "3685     157.0                     85.0                   199.0   \n",
       "3763     150.0                      3.0                   448.0   \n",
       "3766     145.0                      0.0                   392.0   \n",
       "3775     108.0                      0.0                    88.0   \n",
       "3821     148.0                      0.0                   263.0   \n",
       "3890     152.0                    309.0                   132.0   \n",
       "3903     172.0                    120.0                   145.0   \n",
       "3958     168.0                      0.0                    69.0   \n",
       "3970     226.0                    149.0                   248.0   \n",
       "4066     161.0                    767.0                    87.0   \n",
       "4077     186.0                    176.0                   760.0   \n",
       "4157     102.0                    149.0                   357.0   \n",
       "4167     122.0                    149.0                   315.0   \n",
       "4238     172.0                    355.0                   188.0   \n",
       "4351     160.0                    168.0                    71.0   \n",
       "4365     155.0                      0.0                    61.0   \n",
       "4396     113.0                      0.0                   324.0   \n",
       "4498     142.0                      0.0                    24.0   \n",
       "4528     150.0                      6.0                    20.0   \n",
       "4572     167.0                     10.0                    97.0   \n",
       "4584     135.0                      0.0                   310.0   \n",
       "4593     160.0                      5.0                   219.0   \n",
       "4682     106.0                    973.0                    48.0   \n",
       "4694     201.0                      0.0                    84.0   \n",
       "4708     215.0                     14.0                   136.0   \n",
       "4747     202.0                      0.0                     4.0   \n",
       "4897      99.0                      0.0                    93.0   \n",
       "\n",
       "                     actor_2_name  actor_1_facebook_likes        gross  \\\n",
       "0                Joel David Moore                  1000.0  760505847.0   \n",
       "8               Robert Downey Jr.                 26000.0  458991599.0   \n",
       "17              Robert Downey Jr.                 26000.0  623279547.0   \n",
       "20                     Adam Brown                  5000.0  255108370.0   \n",
       "23                     Adam Brown                  5000.0  258355354.0   \n",
       "25             Thomas Kretschmann                  6000.0  218051260.0   \n",
       "26                   Kate Winslet                 29000.0  658672302.0   \n",
       "99                     Adam Brown                  5000.0  303001229.0   \n",
       "105                    Mike Vogel                 87000.0   60655503.0   \n",
       "147                 Orlando Bloom                 11000.0  133228348.0   \n",
       "221   Mary Elizabeth Mastrantonio                   784.0  182618434.0   \n",
       "270                 Orlando Bloom                 16000.0  313837577.0   \n",
       "288             Jenette Goldstein                   780.0  204843350.0   \n",
       "291                   Tia Carrere                  2000.0  146282411.0   \n",
       "337                   AJ Michalka                   873.0   43982842.0   \n",
       "339                    Billy Boyd                  5000.0  377019252.0   \n",
       "340                 Orlando Bloom                 16000.0  340478898.0   \n",
       "399                   Gary Oldman                 11000.0  172620724.0   \n",
       "462               Natalie Portman                 22000.0   95632614.0   \n",
       "499          Brian Anthony Wilson                   766.0   17593391.0   \n",
       "576                  Hal Holbrook                   940.0   27796042.0   \n",
       "606                    Todd Graff                  2000.0   54222000.0   \n",
       "681                Alun Armstrong                   324.0   32598931.0   \n",
       "712                Jeffrey DeMunn                 15000.0  136801374.0   \n",
       "794             Robert Downey Jr.                 26000.0  623279547.0   \n",
       "827                     Al Pacino                 18000.0   60984028.0   \n",
       "883              Bruce Boxleitner                   789.0   12870569.0   \n",
       "895                  Joe Mantegna                 14000.0   66676062.0   \n",
       "957                Morgan Freeman                 18000.0   67823573.0   \n",
       "1051                  Bob Hoskins                 12000.0   25900000.0   \n",
       "...                           ...                     ...          ...   \n",
       "3537                   Bruce Dern                  1000.0          0.0   \n",
       "3575               Brian Thompson                  2000.0   38400000.0   \n",
       "3588              George Chakiris                   804.0   43650000.0   \n",
       "3685            Steven Mackintosh                   397.0    2197331.0   \n",
       "3763               Gedde Watanabe                   859.0    6157157.0   \n",
       "3766                 Woody Strode                   973.0          0.0   \n",
       "3775                   Jed Brophy                 14000.0    3049135.0   \n",
       "3821                Dwight Yoakam                  3000.0   24475416.0   \n",
       "3890               Dorothy Lamour                   232.0   36000000.0   \n",
       "3903             Donald Pleasence                   773.0          0.0   \n",
       "3958                   Ken Howard                   713.0          0.0   \n",
       "3970                George Reeves                   503.0  198655278.0   \n",
       "4066              Sessue Hayakawa                   682.0   27200000.0   \n",
       "4077             Montgomery Clift                   877.0          0.0   \n",
       "4157                        Terry                   695.0   22202612.0   \n",
       "4167              Esther Williams                   760.0          0.0   \n",
       "4238                Teresa Wright                   749.0   23650000.0   \n",
       "4351                         Remo                   733.0      95236.0   \n",
       "4365            T.R. Silambarasan                   141.0          0.0   \n",
       "4396                    Teri Garr                 11000.0          0.0   \n",
       "4498               Luigi Pistilli                 16000.0    6100000.0   \n",
       "4528             Shazahn Padamsee                   964.0          0.0   \n",
       "4572               Manoj Bajpayee                   353.0     610991.0   \n",
       "4584                  AJ Michalka                   873.0   43982842.0   \n",
       "4593                  Anil Kapoor                   724.0      49000.0   \n",
       "4682           Stefania Sandrelli                   319.0          0.0   \n",
       "4694           Thomas Kretschmann                  6000.0  218051260.0   \n",
       "4708                 Jimi Hendrix                   262.0   13300000.0   \n",
       "4747                Minoru Chiaki                   304.0     269061.0   \n",
       "4897           Gian Maria Volontè                 16000.0    3500000.0   \n",
       "\n",
       "                                      genres         ...           \\\n",
       "0            Action|Adventure|Fantasy|Sci-Fi         ...            \n",
       "8                    Action|Adventure|Sci-Fi         ...            \n",
       "17                   Action|Adventure|Sci-Fi         ...            \n",
       "20                         Adventure|Fantasy         ...            \n",
       "23                         Adventure|Fantasy         ...            \n",
       "25            Action|Adventure|Drama|Romance         ...            \n",
       "26                             Drama|Romance         ...            \n",
       "99                         Adventure|Fantasy         ...            \n",
       "105          Action|Adventure|Drama|Thriller         ...            \n",
       "147                                Adventure         ...            \n",
       "221          Action|Adventure|Drama|Thriller         ...            \n",
       "270           Action|Adventure|Drama|Fantasy         ...            \n",
       "288                            Action|Sci-Fi         ...            \n",
       "291                   Action|Comedy|Thriller         ...            \n",
       "337                   Drama|Fantasy|Thriller         ...            \n",
       "339           Action|Adventure|Drama|Fantasy         ...            \n",
       "340           Action|Adventure|Drama|Fantasy         ...            \n",
       "399          Action|Adventure|Drama|Thriller         ...            \n",
       "462      Adventure|Drama|History|Romance|War         ...            \n",
       "499            Action|Adventure|Drama|Sci-Fi         ...            \n",
       "576                            Drama|Romance         ...            \n",
       "606          Adventure|Drama|Sci-Fi|Thriller         ...            \n",
       "681                    Action|Drama|Thriller         ...            \n",
       "712              Crime|Drama|Fantasy|Mystery         ...            \n",
       "794                  Action|Adventure|Sci-Fi         ...            \n",
       "827                   Drama|Mystery|Thriller         ...            \n",
       "883                        Drama|History|War         ...            \n",
       "895                              Crime|Drama         ...            \n",
       "957                    Action|Drama|Thriller         ...            \n",
       "1051                       Crime|Drama|Music         ...            \n",
       "...                                      ...         ...            \n",
       "3537           Comedy|Fantasy|Horror|Mystery         ...            \n",
       "3575                           Action|Sci-Fi         ...            \n",
       "3588    Crime|Drama|Musical|Romance|Thriller         ...            \n",
       "3685            Comedy|Drama|History|Romance         ...            \n",
       "3763                            Comedy|Drama         ...            \n",
       "3766                                 Western         ...            \n",
       "3775  Biography|Crime|Drama|Romance|Thriller         ...            \n",
       "3821                                   Drama         ...            \n",
       "3890                    Drama|Family|Romance         ...            \n",
       "3903    Adventure|Drama|History|Thriller|War         ...            \n",
       "3958            Drama|Family|History|Musical         ...            \n",
       "3970               Drama|History|Romance|War         ...            \n",
       "4066                     Adventure|Drama|War         ...            \n",
       "4077                               Drama|War         ...            \n",
       "4157        Adventure|Family|Fantasy|Musical         ...            \n",
       "4167               Drama|Fantasy|Romance|War         ...            \n",
       "4238                       Drama|Romance|War         ...            \n",
       "4351                           Drama|Musical         ...            \n",
       "4365                          Comedy|Romance         ...            \n",
       "4396                  Drama|Mystery|Thriller         ...            \n",
       "4498                                 Western         ...            \n",
       "4528                            Comedy|Drama         ...            \n",
       "4572                           Drama|Romance         ...            \n",
       "4584                  Drama|Fantasy|Thriller         ...            \n",
       "4593                                Thriller         ...            \n",
       "4682                                   Drama         ...            \n",
       "4694          Action|Adventure|Drama|Romance         ...            \n",
       "4708               Documentary|History|Music         ...            \n",
       "4747                  Action|Adventure|Drama         ...            \n",
       "4897                    Action|Drama|Western         ...            \n",
       "\n",
       "     num_user_for_reviews  language      country  content_rating       budget  \\\n",
       "0                  3054.0   English          USA           PG-13  237000000.0   \n",
       "8                  1117.0   English          USA           PG-13  250000000.0   \n",
       "17                 1722.0   English          USA           PG-13  220000000.0   \n",
       "20                  802.0   English  New Zealand           PG-13  250000000.0   \n",
       "23                  951.0   English          USA           PG-13  225000000.0   \n",
       "25                 2618.0   English  New Zealand           PG-13  207000000.0   \n",
       "26                 2528.0   English          USA           PG-13  200000000.0   \n",
       "99                 1367.0   English          USA           PG-13  180000000.0   \n",
       "105                 629.0   English          USA           PG-13  160000000.0   \n",
       "147                1694.0   English          USA               R  175000000.0   \n",
       "221                 779.0   English          USA           PG-13  140000000.0   \n",
       "270                5060.0   English  New Zealand           PG-13   93000000.0   \n",
       "288                 983.0   English          USA               R  102000000.0   \n",
       "291                 351.0   English          USA               R  115000000.0   \n",
       "337                 593.0   English          USA           PG-13   65000000.0   \n",
       "339                3189.0   English          USA           PG-13   94000000.0   \n",
       "340                2417.0   English          USA           PG-13   94000000.0   \n",
       "399                 393.0   English          USA               R   85000000.0   \n",
       "462                 674.0   English          USA               R   79000000.0   \n",
       "499                 376.0   English          USA               R   80000000.0   \n",
       "576                 376.0   English          USA              PG   72000000.0   \n",
       "606                 380.0   English          USA           PG-13   69500000.0   \n",
       "681                 265.0   English          USA               R   65000000.0   \n",
       "712                1377.0   English          USA               R   60000000.0   \n",
       "794                1722.0   English          USA           PG-13  220000000.0   \n",
       "827                 431.0   English          USA               R   57000000.0   \n",
       "883                 497.0   English          USA           PG-13   56000000.0   \n",
       "895                 545.0   English          USA               R   54000000.0   \n",
       "957                 130.0   English          USA               R   50000000.0   \n",
       "1051                 84.0   English          USA               R   58000000.0   \n",
       "...                   ...       ...          ...             ...          ...   \n",
       "3537                 70.0   English          USA               R    7000000.0   \n",
       "3575                692.0   English           UK               R    6500000.0   \n",
       "3588                316.0   English          USA         Unrated    6000000.0   \n",
       "3685                321.0     Hindi        India       Not Rated          0.0   \n",
       "3763                198.0   English          USA           PG-13    5000000.0   \n",
       "3766                565.0   English        Italy           PG-13    5000000.0   \n",
       "3775                265.0   English  New Zealand               R    5000000.0   \n",
       "3821                309.0   English          USA               R     890000.0   \n",
       "3890                107.0   English          USA       Not Rated    4000000.0   \n",
       "3903                301.0   English          USA        Approved    4000000.0   \n",
       "3958                129.0   English          USA              PG    4000000.0   \n",
       "3970                706.0   English          USA               G    3977000.0   \n",
       "4066                273.0   English           UK              PG    3000000.0   \n",
       "4077                176.0   English          USA       Not Rated    3000000.0   \n",
       "4157                533.0   English          USA          Passed    2800000.0   \n",
       "4167                 27.0   English          USA          Passed    2627000.0   \n",
       "4238                235.0   English          USA       Not Rated    2100000.0   \n",
       "4351                 38.0     Hindi        India       Not Rated          0.0   \n",
       "4365                  6.0     Tamil        India               0  150000000.0   \n",
       "4396                313.0   English          USA              PG    1600000.0   \n",
       "4498                780.0   Italian        Italy        Approved    1200000.0   \n",
       "4528                 35.0     Hindi        India               0          0.0   \n",
       "4572                 19.0     Hindi        India               0    1000000.0   \n",
       "4584                593.0   English          USA           PG-13   65000000.0   \n",
       "4593                 30.0     Hindi        India               0    1500000.0   \n",
       "4682                101.0   Italian        Italy               R     750000.0   \n",
       "4694               2618.0   English  New Zealand           PG-13  207000000.0   \n",
       "4708                 63.0   English          USA               R     600000.0   \n",
       "4747                596.0  Japanese        Japan         Unrated    2000000.0   \n",
       "4897                235.0   Italian        Italy               R     200000.0   \n",
       "\n",
       "      title_year actor_2_facebook_likes imdb_score  aspect_ratio  \\\n",
       "0         2009.0                  936.0        7.9          1.78   \n",
       "8         2015.0                21000.0        7.5          2.35   \n",
       "17        2012.0                21000.0        8.1          1.85   \n",
       "20        2014.0                  972.0        7.5          2.35   \n",
       "23        2013.0                  972.0        7.9          2.35   \n",
       "25        2005.0                  919.0        7.2          2.35   \n",
       "26        1997.0                14000.0        7.7          2.35   \n",
       "99        2012.0                  972.0        7.9          2.35   \n",
       "105       2006.0                 2000.0        5.6          2.35   \n",
       "147       2004.0                 5000.0        7.2          2.35   \n",
       "221       2000.0                  638.0        6.4          2.35   \n",
       "270       2001.0                 5000.0        8.8          2.35   \n",
       "288       1991.0                  604.0        8.5          2.35   \n",
       "291       1994.0                 1000.0        7.2          2.35   \n",
       "337       2009.0                  560.0        6.7          2.35   \n",
       "339       2003.0                  857.0        8.9          2.35   \n",
       "340       2002.0                 5000.0        8.7          2.35   \n",
       "399       1997.0                10000.0        6.4          2.35   \n",
       "462       2003.0                20000.0        7.2          2.35   \n",
       "499       1997.0                  674.0        6.0          2.35   \n",
       "576       2001.0                  826.0        6.9          1.85   \n",
       "606       1989.0                  650.0        7.6          2.35   \n",
       "681       2000.0                  192.0        6.2          2.35   \n",
       "712       1999.0                  745.0        8.5          1.85   \n",
       "794       2012.0                21000.0        8.1          1.85   \n",
       "827       1997.0                14000.0        7.5          2.35   \n",
       "883       2003.0                  640.0        6.3          2.35   \n",
       "895       1990.0                 1000.0        7.6          1.85   \n",
       "957       1995.0                11000.0        6.6          1.85   \n",
       "1051      1984.0                 5000.0        6.5          1.85   \n",
       "...          ...                    ...        ...           ...   \n",
       "3537      2011.0                  844.0        4.8          1.85   \n",
       "3575      1984.0                  663.0        8.1          1.85   \n",
       "3588      1961.0                  271.0        7.6          2.20   \n",
       "3685      2006.0                  227.0        8.4          2.35   \n",
       "3763      1989.0                  448.0        7.0          1.85   \n",
       "3766      1968.0                  423.0        8.6          2.35   \n",
       "3775      1994.0                  433.0        7.4          2.35   \n",
       "3821      1996.0                  324.0        8.0          1.85   \n",
       "3890      1952.0                  178.0        6.7          1.37   \n",
       "3903      1963.0                  742.0        8.3          2.35   \n",
       "3958      1972.0                  649.0        7.6          2.35   \n",
       "3970      1939.0                  384.0        8.2          1.37   \n",
       "4066      1957.0                  119.0        8.2          2.35   \n",
       "4077      1961.0                  862.0        8.3          1.75   \n",
       "4157      1939.0                  421.0        8.1          1.37   \n",
       "4167      1943.0                  675.0        7.0          1.37   \n",
       "4238      1946.0                  208.0        8.1          1.37   \n",
       "4351      2013.0                  168.0        6.4          0.00   \n",
       "4365      2015.0                   77.0        5.1          0.00   \n",
       "4396      1974.0                  481.0        7.9          1.37   \n",
       "4498      1966.0                   34.0        8.9          2.35   \n",
       "4528      2009.0                   22.0        7.5          0.00   \n",
       "4572      2000.0                  186.0        6.2          2.35   \n",
       "4584      2009.0                  559.0        6.7          2.35   \n",
       "4593      2005.0                  668.0        4.8          0.00   \n",
       "4682      1970.0                   90.0        8.1          1.66   \n",
       "4694      2005.0                  918.0        7.2          2.35   \n",
       "4708      1970.0                  227.0        8.1          2.20   \n",
       "4747      1954.0                    8.0        8.7          1.37   \n",
       "4897      1964.0                  360.0        8.0          2.35   \n",
       "\n",
       "     movie_facebook_likes  \n",
       "0                   33000  \n",
       "8                  118000  \n",
       "17                 123000  \n",
       "20                  65000  \n",
       "23                  83000  \n",
       "25                      0  \n",
       "26                  26000  \n",
       "99                 166000  \n",
       "105                     0  \n",
       "147                     0  \n",
       "221                     0  \n",
       "270                 21000  \n",
       "288                 13000  \n",
       "291                     0  \n",
       "337                 16000  \n",
       "339                 16000  \n",
       "340                 10000  \n",
       "399                     0  \n",
       "462                     0  \n",
       "499                     0  \n",
       "576                     0  \n",
       "606                     0  \n",
       "681                   892  \n",
       "712                 30000  \n",
       "794                123000  \n",
       "827                 11000  \n",
       "883                   953  \n",
       "895                     0  \n",
       "957                     0  \n",
       "1051                  828  \n",
       "...                   ...  \n",
       "3537                    0  \n",
       "3575                13000  \n",
       "3588                    0  \n",
       "3685                    0  \n",
       "3763                    0  \n",
       "3766                10000  \n",
       "3775                    0  \n",
       "3821                    0  \n",
       "3890                  625  \n",
       "3903                 8000  \n",
       "3958                    0  \n",
       "3970                16000  \n",
       "4066                    0  \n",
       "4077                    0  \n",
       "4157                14000  \n",
       "4167                  116  \n",
       "4238                    0  \n",
       "4351                 1000  \n",
       "4365                   82  \n",
       "4396                 6000  \n",
       "4498                20000  \n",
       "4528                  773  \n",
       "4572                   92  \n",
       "4584                16000  \n",
       "4593                   31  \n",
       "4682                    0  \n",
       "4694                    0  \n",
       "4708                    0  \n",
       "4747                11000  \n",
       "4897                    0  \n",
       "\n",
       "[124 rows x 28 columns]"
      ]
     },
     "execution_count": 172,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grouped.filter(lambda g : g['duration'].mean() >= 150)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 表联结\n",
    "提供了类似于SQL的join接口，供我们进行多表组合。不同的是，pandas可以对index进行join"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Concatenate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <td>D2</td>\n",
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       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A5</td>\n",
       "      <td>B5</td>\n",
       "      <td>C5</td>\n",
       "      <td>D5</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A6</td>\n",
       "      <td>B6</td>\n",
       "      <td>C6</td>\n",
       "      <td>D6</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>A7</td>\n",
       "      <td>B7</td>\n",
       "      <td>C7</td>\n",
       "      <td>D7</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "     A    B    C    D    A    B    C    D\n",
       "0   A0   B0   C0   D0  NaN  NaN  NaN  NaN\n",
       "1   A1   B1   C1   D1  NaN  NaN  NaN  NaN\n",
       "2   A2   B2   C2   D2  NaN  NaN  NaN  NaN\n",
       "3   A3   B3   C3   D3  NaN  NaN  NaN  NaN\n",
       "4  NaN  NaN  NaN  NaN   A4   B4   C4   D4\n",
       "5  NaN  NaN  NaN  NaN   A5   B5   C5   D5\n",
       "6  NaN  NaN  NaN  NaN   A6   B6   C6   D6\n",
       "7  NaN  NaN  NaN  NaN   A7   B7   C7   D7"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 样本数据\n",
    "df1 = pd.DataFrame({'A': ['A0', 'A1', 'A2', 'A3'],\n",
    "                     'B': ['B0', 'B1', 'B2', 'B3'],\n",
    "                     'C': ['C0', 'C1', 'C2', 'C3'],\n",
    "                     'D': ['D0', 'D1', 'D2', 'D3']},\n",
    "                     index=[0, 1, 2, 3])\n",
    " \n",
    "\n",
    "df2 = pd.DataFrame({'A': ['A4', 'A5', 'A6', 'A7'],\n",
    "                     'B': ['B4', 'B5', 'B6', 'B7'],\n",
    "                     'C': ['C4', 'C5', 'C6', 'C7'],\n",
    "                     'D': ['D4', 'D5', 'D6', 'D7']},\n",
    "                      index=[4, 5, 6, 7])\n",
    " \n",
    "\n",
    "df3 = pd.DataFrame({'A': ['A8', 'A9', 'A10', 'A11'],\n",
    "                     'B': ['B8', 'B9', 'B10', 'B11'],\n",
    "                     'C': ['C8', 'C9', 'C10', 'C11'],\n",
    "                     'D': ['D8', 'D9', 'D10', 'D11']},\n",
    "                     index=[8, 9, 10, 11])\n",
    "\n",
    "df4 = pd.DataFrame({'A': ['A8', 'A9', 'A10', 'A11'],\n",
    "                     'B': ['B8', 'B9', 'B10', 'B11'],\n",
    "                     'C': ['C8', 'C9', 'C10', 'C11'],\n",
    "                     'D': ['D8', 'D9', 'D10', 'D11']},\n",
    "                     index=[0, 1, 2, 3])\n",
    "\n",
    "#result = pd.concat([df1,df2,df3],axis=0)\n",
    "result = pd.concat([df1,df2],axis=1)\n",
    "result = pd.merge(df1,df2,left_index=True,right_index=True,how='outer')\n",
    "result = pd.merge(df1,df4,left_index=True,right_index=True,how='inner')\n",
    "result"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<img src=\"http://pandas.pydata.org/pandas-docs/stable/_images/merging_concat_basic.png\" width = \"400\" height = \"300\" alt=\"图片名称\" align=left />"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.concat(objs, axis=0, join='outer', join_axes=None, ignore_index=False,\n",
    "          keys=None, levels=None, names=None, verify_integrity=False,\n",
    "          copy=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Database-style DataFrame joining/merging\n",
    "\n",
    "merge函数用来对两张表进行join，非常类似于sql当中的表联结。 pandas里面不仅可以对columns进行Join,还可以对index进行join。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "pd.merge(left, right, how='inner', on=None, left_on=None, right_on=None,\n",
    "         left_index=False, right_index=False, sort=True,\n",
    "         suffixes=('_x', '_y'), copy=True, indicator=False,\n",
    "         validate=None)\n",
    "```\n",
    "\n",
    "* left: A DataFrame object\n",
    "\n",
    "* right: Another DataFrame object\n",
    "\n",
    "* on: Columns (names) to join on. Must be found in both the left and right DataFrame objects. If not passed and left_index and right_index are False, the intersection of the columns in the DataFrames will be inferred to be the join keys\n",
    "\n",
    "* left_on: Columns from the left DataFrame to use as keys. Can either be column names or arrays with length equal to the length of the DataFrame\n",
    "\n",
    "* right_on: Columns from the right DataFrame to use as keys. Can either be column names or arrays with length equal to the length of the DataFrame\n",
    "\n",
    "* left_index: If True, use the index (row labels) from the left DataFrame as its join key(s). In the case of a DataFrame with a MultiIndex (hierarchical), the number of levels must match the number of join keys from the right DataFrame\n",
    "\n",
    "* right_index: Same usage as left_index for the right DataFrame\n",
    "\n",
    "* how: One of 'left', 'right', 'outer', 'inner'. Defaults to inner. See below for more detailed description of each method\n",
    "\n",
    "* sort: Sort the result DataFrame by the join keys in lexicographical order. Defaults to True, setting to False will improve performance substantially in many cases\n",
    "\n",
    "* suffixes: A tuple of string suffixes to apply to overlapping columns. Defaults to ('_x', '_y').\n",
    "\n",
    "* copy: Always copy data (default True) from the passed DataFrame objects, even when reindexing is not necessary. Cannot be avoided in many cases but may improve performance / memory usage. The cases where copying can be avoided are somewhat pathological but this option is provided nonetheless.\n",
    "\n",
    "* indicator: Add a column to the output DataFrame called _merge with information on the source of each row. _merge is Categorical-type and takes on a value of left_only for observations whose merge key only appears in 'left' DataFrame, right_only for observations whose merge key only appears in 'right' DataFrame, and both if the observation’s merge key is found in both."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "solution": "shown",
    "solution_first": true
   },
   "outputs": [],
   "source": [
    "# 在一个主键上进行join\n",
    "left = pd.DataFrame({'key': ['K0', 'K1', 'K2', 'K3'],\n",
    "                      'A': ['A0', 'A1', 'A2', 'A3'],\n",
    "                      'B': ['B0', 'B1', 'B2', 'B3']})\n",
    "\n",
    "\n",
    "right = pd.DataFrame({'key': ['K0', 'K1', 'K2', 'K3'],\n",
    "                       'C': ['C0', 'C1', 'C2', 'C3'],\n",
    "                       'D': ['D0', 'D1', 'D2', 'D3']})\n",
    " \n",
    "\n",
    "result = pd.merge(left, right, on='key')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "solution": "shown"
   },
   "source": [
    "![r1](http://pandas.pydata.org/pandas-docs/stable/_images/merging_merge_on_key.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "solution": "hidden",
    "solution_first": true
   },
   "outputs": [],
   "source": [
    "# 在多个主键上Join\n",
    "left = pd.DataFrame({'key1': ['K0', 'K0', 'K1', 'K2'],\n",
    "                      'key2': ['K0', 'K1', 'K0', 'K1'],\n",
    "                      'A': ['A0', 'A1', 'A2', 'A3'],\n",
    "                      'B': ['B0', 'B1', 'B2', 'B3']})\n",
    " \n",
    "\n",
    "right = pd.DataFrame({'key1': ['K0', 'K1', 'K1', 'K2'],\n",
    "                       'key2': ['K0', 'K0', 'K0', 'K0'],\n",
    "                       'C': ['C0', 'C1', 'C2', 'C3'],\n",
    "                       'D': ['D0', 'D1', 'D2', 'D3']})\n",
    " \n",
    "\n",
    "result = pd.merge(left, right, on=['key1', 'key2'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "solution": "hidden"
   },
   "source": [
    "![r2](http://pandas.pydata.org/pandas-docs/stable/_images/merging_merge_on_key_multiple.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "solution": "hidden",
    "solution_first": true
   },
   "outputs": [],
   "source": [
    "result = pd.merge(left, right, how='left', on=['key1', 'key2'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "solution": "hidden"
   },
   "source": [
    "![r3](http://pandas.pydata.org/pandas-docs/stable/_images/merging_merge_on_key_left.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "solution": "shown",
    "solution_first": true
   },
   "outputs": [],
   "source": [
    "result = pd.merge(left, right, how='right', on=['key1', 'key2'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "solution": "shown"
   },
   "source": [
    "![r4](http://pandas.pydata.org/pandas-docs/stable/_images/merging_merge_on_key_outer.png)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "solution": "shown",
    "solution_first": true
   },
   "outputs": [],
   "source": [
    "result = pd.merge(left, right, how='outer', on=['key1', 'key2'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "** joining on index**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 175,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "left = pd.DataFrame({'key1': ['K0', 'K0', 'K1', 'K2'],\n",
    "                      'key2': ['K0', 'K1', 'K0', 'K1'],\n",
    "                      'A': ['A0', 'A1', 'A2', 'A3'],\n",
    "                      'B': ['B0', 'B1', 'B2', 'B3']})\n",
    " \n",
    "\n",
    "right = pd.DataFrame({'key1': ['K0', 'K1', 'K1', 'K2'],\n",
    "                       'key2': ['K0', 'K0', 'K0', 'K0'],\n",
    "                       'C': ['C0', 'C1', 'C2', 'C3'],\n",
    "                       'D': ['D0', 'D1', 'D2', 'D3']})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 178,
   "metadata": {},
   "outputs": [],
   "source": [
    "left.set_index([\"key1\",\"key2\"],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 179,
   "metadata": {},
   "outputs": [],
   "source": [
    "right.set_index([\"key1\",\"key2\"],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 182,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>key1</th>\n",
       "      <th>key2</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>K0</th>\n",
       "      <th>K0</th>\n",
       "      <td>A0</td>\n",
       "      <td>B0</td>\n",
       "      <td>C0</td>\n",
       "      <td>D0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"2\" valign=\"top\">K1</th>\n",
       "      <th>K0</th>\n",
       "      <td>A2</td>\n",
       "      <td>B2</td>\n",
       "      <td>C1</td>\n",
       "      <td>D1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>K0</th>\n",
       "      <td>A2</td>\n",
       "      <td>B2</td>\n",
       "      <td>C2</td>\n",
       "      <td>D2</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            A   B   C   D\n",
       "key1 key2                \n",
       "K0   K0    A0  B0  C0  D0\n",
       "K1   K0    A2  B2  C1  D1\n",
       "     K0    A2  B2  C2  D2"
      ]
     },
     "execution_count": 182,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(left,right,left_index=True,right_index=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 188,
   "metadata": {},
   "outputs": [],
   "source": [
    "left = pd.DataFrame({'key1': ['K0', 'K0', 'K1', 'K2'],\n",
    "                      'key2': ['K0', 'K1', 'K0', 'K1'],\n",
    "                      'A': ['A0', 'A1', 'A2', 'A3'],\n",
    "                      'B': ['B0', 'B1', 'B2', 'B3']})\n",
    " \n",
    "\n",
    "right = pd.DataFrame({'key3': ['K0', 'K1', 'K1', 'K2'],\n",
    "                       'key4': ['K0', 'K0', 'K0', 'K0'],\n",
    "                       'C': ['C0', 'C1', 'C2', 'C3'],\n",
    "                       'D': ['D0', 'D1', 'D2', 'D3']})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 191,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>key1</th>\n",
       "      <th>key2</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>key3</th>\n",
       "      <th>key4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A0</td>\n",
       "      <td>B0</td>\n",
       "      <td>K0</td>\n",
       "      <td>K0</td>\n",
       "      <td>C0</td>\n",
       "      <td>D0</td>\n",
       "      <td>K0</td>\n",
       "      <td>K0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A2</td>\n",
       "      <td>B2</td>\n",
       "      <td>K1</td>\n",
       "      <td>K0</td>\n",
       "      <td>C1</td>\n",
       "      <td>D1</td>\n",
       "      <td>K1</td>\n",
       "      <td>K0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A2</td>\n",
       "      <td>B2</td>\n",
       "      <td>K1</td>\n",
       "      <td>K0</td>\n",
       "      <td>C2</td>\n",
       "      <td>D2</td>\n",
       "      <td>K1</td>\n",
       "      <td>K0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    A   B key1 key2   C   D key3 key4\n",
       "0  A0  B0   K0   K0  C0  D0   K0   K0\n",
       "1  A2  B2   K1   K0  C1  D1   K1   K0\n",
       "2  A2  B2   K1   K0  C2  D2   K1   K0"
      ]
     },
     "execution_count": 191,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(left,right,left_on = ['key1','key2'],right_on = ['key3','key4'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 192,
   "metadata": {},
   "outputs": [],
   "source": [
    "left.set_index([\"key1\",\"key2\"],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 194,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>A</th>\n",
       "      <th>B</th>\n",
       "      <th>C</th>\n",
       "      <th>D</th>\n",
       "      <th>key3</th>\n",
       "      <th>key4</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>A0</td>\n",
       "      <td>B0</td>\n",
       "      <td>C0</td>\n",
       "      <td>D0</td>\n",
       "      <td>K0</td>\n",
       "      <td>K0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A2</td>\n",
       "      <td>B2</td>\n",
       "      <td>C1</td>\n",
       "      <td>D1</td>\n",
       "      <td>K1</td>\n",
       "      <td>K0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>A2</td>\n",
       "      <td>B2</td>\n",
       "      <td>C2</td>\n",
       "      <td>D2</td>\n",
       "      <td>K1</td>\n",
       "      <td>K0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    A   B   C   D key3 key4\n",
       "0  A0  B0  C0  D0   K0   K0\n",
       "1  A2  B2  C1  D1   K1   K0\n",
       "2  A2  B2  C2  D2   K1   K0"
      ]
     },
     "execution_count": 194,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.merge(left,right,left_index = True,right_on=['key3','key4'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr>\n",
       "      <th>K2</th>\n",
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      "text/plain": [
       "            A   B\n",
       "key1 key2        \n",
       "K0   K0    A0  B0\n",
       "     K1    A1  B1\n",
       "K1   K0    A2  B2\n",
       "K2   K1    A3  B3"
      ]
     },
     "execution_count": 193,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "left"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 189,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    C   D key3 key4\n",
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       "2  C2  D2   K1   K0\n",
       "3  C3  D3   K2   K0"
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   "source": [
    "right"
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  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 数据透视"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**pivot_table** 提供了类似于EXCEL数据透视表的功能，重点的参数如下:\n",
    "\n",
    "* data: A DataFrame object\n",
    "* values: a column or a list of columns to aggregate\n",
    "* index: a column, Grouper, array which has the same length as data, or list of them. Keys to group by on the pivot table index. If an array is passed, it is being used as the same manner as column values.\n",
    "* columns: a column, Grouper, array which has the same length as data, or list of them. Keys to group by on the pivot table column. If an array is passed, it is being used as the same manner as column values.\n",
    "* aggfunc: function to use for aggregation, defaulting to numpy.mean"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**crosstab** 用于计算两个以上的因子的cross-tabulation. 默认的是计算因子之间的频率，除非指定了其它数组或者函数进行计算\n",
    "\n",
    "* index: array-like, values to group by in the rows\n",
    "* columns: array-like, values to group by in the columns\n",
    "* values: array-like, optional, array of values to aggregate according to the factors\n",
    "* aggfunc: function, optional, If no values array is passed, computes a frequency table\n",
    "* rownames: sequence, default None, must match number of row arrays passed\n",
    "* colnames: sequence, default None, if passed, must match number of column arrays passed\n",
    "* margins: boolean, default False, Add row/column margins (subtotals)\n",
    "* normalize: boolean, {‘all’, ‘index’, ‘columns’}, or {0,1}, default False. Normalize by dividing all values by the sum of values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [
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       "    <tr>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>William Shatner</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>William Wyler</th>\n",
       "      <td>1</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Wilson Yip</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
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       "      <td>1</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>Wolfgang Petersen</th>\n",
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       "      <td>7</td>\n",
       "      <td>7</td>\n",
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       "      <td>1</td>\n",
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       "    <tr>\n",
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       "    <tr>\n",
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       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>Xavier Gens</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
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       "    <tr>\n",
       "      <th>Yarrow Cheney</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yash Chopra</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yimou Zhang</th>\n",
       "      <td>2</td>\n",
       "      <td>6</td>\n",
       "      <td>8</td>\n",
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       "    <tr>\n",
       "      <th>Yorgos Lanthimos</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "      <th>Youssef Delara</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Yuefeng Song</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zach Braff</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zach Cregger</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>Zack Snyder</th>\n",
       "      <td>0</td>\n",
       "      <td>8</td>\n",
       "      <td>8</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zack Ward</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zak Penn</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zal Batmanglij</th>\n",
       "      <td>0</td>\n",
       "      <td>2</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Zoran Lisinac</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Álex de la Iglesia</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Émile Gaudreault</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Éric Tessier</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>Étienne Faure</th>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>All</th>\n",
       "      <td>206</td>\n",
       "      <td>4716</td>\n",
       "      <td>4922</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2388 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "color                        Black and White  Color   All\n",
       "director_name                                            \n",
       "A. Raven Cruz                              0      1     1\n",
       "Aaron Hann                                 0      1     1\n",
       "Aaron Schneider                            0      1     1\n",
       "Aaron Seltzer                              0      1     1\n",
       "Abel Ferrara                               0      1     1\n",
       "Adam Brooks                                0      1     1\n",
       "Adam Carolla                               0      1     1\n",
       "Adam Goldberg                              0      1     1\n",
       "Adam Green                                 0      1     1\n",
       "Adam Jay Epstein                           0      1     1\n",
       "Adam Marcus                                0      1     1\n",
       "Adam McKay                                 0      6     6\n",
       "Adam Rapp                                  0      1     1\n",
       "Adam Rifkin                                0      2     2\n",
       "Adam Shankman                              0      8     8\n",
       "Adrian Lyne                                0      4     4\n",
       "Adrienne Shelly                            0      1     1\n",
       "Agnieszka Holland                          0      1     1\n",
       "Agnieszka Wojtowicz-Vosloo                 0      1     1\n",
       "Agustín Díaz Yanes                         0      1     1\n",
       "Aki Kaurismäki                             0      1     1\n",
       "Akira Kurosawa                             1      1     2\n",
       "Akiva Goldsman                             0      1     1\n",
       "Akiva Schaffer                             0      3     3\n",
       "Al Franklin                                0      1     1\n",
       "Al Silliman Jr.                            0      1     1\n",
       "Alain Resnais                              0      1     1\n",
       "Alan Alda                                  0      1     1\n",
       "Alan Cohn                                  0      1     1\n",
       "Alan J. Pakula                             0      2     2\n",
       "...                                      ...    ...   ...\n",
       "William Phillips                           0      1     1\n",
       "William Sachs                              0      1     1\n",
       "William Shatner                            0      1     1\n",
       "William Wyler                              1      0     1\n",
       "Wilson Yip                                 0      1     1\n",
       "Wolfgang Becker                            1      0     1\n",
       "Wolfgang Petersen                          0      7     7\n",
       "Woo-Suk Kang                               0      1     1\n",
       "Woody Allen                                2     20    22\n",
       "Wych Kaosayananda                          0      1     1\n",
       "Xavier Beauvois                            0      1     1\n",
       "Xavier Gens                                0      2     2\n",
       "Yarrow Cheney                              0      1     1\n",
       "Yash Chopra                                0      2     2\n",
       "Yimou Zhang                                2      6     8\n",
       "Yorgos Lanthimos                           0      1     1\n",
       "Youssef Delara                             0      2     2\n",
       "Yuefeng Song                               0      1     1\n",
       "Zach Braff                                 0      2     2\n",
       "Zach Cregger                               0      1     1\n",
       "Zack Snyder                                0      8     8\n",
       "Zack Ward                                  0      1     1\n",
       "Zak Penn                                   0      1     1\n",
       "Zal Batmanglij                             0      2     2\n",
       "Zoran Lisinac                              0      1     1\n",
       "Álex de la Iglesia                         0      1     1\n",
       "Émile Gaudreault                           0      1     1\n",
       "Éric Tessier                               0      1     1\n",
       "Étienne Faure                              0      1     1\n",
       "All                                      206   4716  4922\n",
       "\n",
       "[2388 rows x 3 columns]"
      ]
     },
     "execution_count": 202,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "pd.crosstab(df['director_name'],df['color'],margins=True)"
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       "      <th colspan=\"10\" halign=\"left\">director_facebook_likes</th>\n",
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       "      <th>A. Raven Cruz</th>\n",
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       "      <td>NaN</td>\n",
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       "      <td>20.0</td>\n",
       "      <td>102.0</td>\n",
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       "      <td>134.0</td>\n",
       "      <td>0.0</td>\n",
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      "text/plain": [
       "                                     sum                             \\\n",
       "                 director_facebook_likes                              \n",
       "director_name              A. Raven Cruz Aaron Hann Aaron Schneider   \n",
       "color                                                                 \n",
       " Black and White                     NaN        NaN             NaN   \n",
       "Color                                0.0        0.0            11.0   \n",
       "\n",
       "                                                                      \\\n",
       "                                                                       \n",
       "director_name    Aaron Seltzer Abel Ferrara Adam Brooks Adam Carolla   \n",
       "color                                                                  \n",
       " Black and White           NaN          NaN         NaN          NaN   \n",
       "Color                     64.0        220.0        20.0        102.0   \n",
       "\n",
       "                                                                ...       \\\n",
       "                                                                ...        \n",
       "director_name    Adam Goldberg Adam Green Adam Jay Epstein      ...        \n",
       "color                                                           ...        \n",
       " Black and White           NaN        NaN              NaN      ...        \n",
       "Color                   1000.0      134.0              0.0      ...        \n",
       "\n",
       "                         mean                                                \\\n",
       "                     duration                                                 \n",
       "director_name    Zach Cregger Zack Snyder Zack Ward Zak Penn Zal Batmanglij   \n",
       "color                                                                         \n",
       " Black and White          NaN         NaN       NaN      NaN            NaN   \n",
       "Color                    90.0     138.375      92.0     94.0          100.5   \n",
       "\n",
       "                                                                    \\\n",
       "                                                                     \n",
       "director_name    Zoran Lisinac Álex de la Iglesia Émile Gaudreault   \n",
       "color                                                                \n",
       " Black and White           NaN                NaN              NaN   \n",
       "Color                    108.0              104.0             92.0   \n",
       "\n",
       "                                             \n",
       "                                             \n",
       "director_name    Éric Tessier Étienne Faure  \n",
       "color                                        \n",
       " Black and White          NaN           NaN  \n",
       "Color                    99.0          98.0  \n",
       "\n",
       "[2 rows x 9539 columns]"
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     "execution_count": 200,
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   ]
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